example would be, if User A has shares = 1024 and user
B has shares = 2048, User B will get twice the CPU
bandwidth user A will. For more details refer
- Documentation/scheduler/sched-design-CFS.txt
+ Documentation/scheduler/sched-design-CFS.rst
--- /dev/null
+================================================
+Completions - "wait for completion" barrier APIs
+================================================
+
+Introduction:
+-------------
+
+If you have one or more threads that must wait for some kernel activity
+to have reached a point or a specific state, completions can provide a
+race-free solution to this problem. Semantically they are somewhat like a
+pthread_barrier() and have similar use-cases.
+
+Completions are a code synchronization mechanism which is preferable to any
+misuse of locks/semaphores and busy-loops. Any time you think of using
+yield() or some quirky msleep(1) loop to allow something else to proceed,
+you probably want to look into using one of the wait_for_completion*()
+calls and complete() instead.
+
+The advantage of using completions is that they have a well defined, focused
+purpose which makes it very easy to see the intent of the code, but they
+also result in more efficient code as all threads can continue execution
+until the result is actually needed, and both the waiting and the signalling
+is highly efficient using low level scheduler sleep/wakeup facilities.
+
+Completions are built on top of the waitqueue and wakeup infrastructure of
+the Linux scheduler. The event the threads on the waitqueue are waiting for
+is reduced to a simple flag in 'struct completion', appropriately called "done".
+
+As completions are scheduling related, the code can be found in
+kernel/sched/completion.c.
+
+
+Usage:
+------
+
+There are three main parts to using completions:
+
+ - the initialization of the 'struct completion' synchronization object
+ - the waiting part through a call to one of the variants of wait_for_completion(),
+ - the signaling side through a call to complete() or complete_all().
+
+There are also some helper functions for checking the state of completions.
+Note that while initialization must happen first, the waiting and signaling
+part can happen in any order. I.e. it's entirely normal for a thread
+to have marked a completion as 'done' before another thread checks whether
+it has to wait for it.
+
+To use completions you need to #include <linux/completion.h> and
+create a static or dynamic variable of type 'struct completion',
+which has only two fields::
+
+ struct completion {
+ unsigned int done;
+ wait_queue_head_t wait;
+ };
+
+This provides the ->wait waitqueue to place tasks on for waiting (if any), and
+the ->done completion flag for indicating whether it's completed or not.
+
+Completions should be named to refer to the event that is being synchronized on.
+A good example is::
+
+ wait_for_completion(&early_console_added);
+
+ complete(&early_console_added);
+
+Good, intuitive naming (as always) helps code readability. Naming a completion
+'complete' is not helpful unless the purpose is super obvious...
+
+
+Initializing completions:
+-------------------------
+
+Dynamically allocated completion objects should preferably be embedded in data
+structures that are assured to be alive for the life-time of the function/driver,
+to prevent races with asynchronous complete() calls from occurring.
+
+Particular care should be taken when using the _timeout() or _killable()/_interruptible()
+variants of wait_for_completion(), as it must be assured that memory de-allocation
+does not happen until all related activities (complete() or reinit_completion())
+have taken place, even if these wait functions return prematurely due to a timeout
+or a signal triggering.
+
+Initializing of dynamically allocated completion objects is done via a call to
+init_completion()::
+
+ init_completion(&dynamic_object->done);
+
+In this call we initialize the waitqueue and set ->done to 0, i.e. "not completed"
+or "not done".
+
+The re-initialization function, reinit_completion(), simply resets the
+->done field to 0 ("not done"), without touching the waitqueue.
+Callers of this function must make sure that there are no racy
+wait_for_completion() calls going on in parallel.
+
+Calling init_completion() on the same completion object twice is
+most likely a bug as it re-initializes the queue to an empty queue and
+enqueued tasks could get "lost" - use reinit_completion() in that case,
+but be aware of other races.
+
+For static declaration and initialization, macros are available.
+
+For static (or global) declarations in file scope you can use
+DECLARE_COMPLETION()::
+
+ static DECLARE_COMPLETION(setup_done);
+ DECLARE_COMPLETION(setup_done);
+
+Note that in this case the completion is boot time (or module load time)
+initialized to 'not done' and doesn't require an init_completion() call.
+
+When a completion is declared as a local variable within a function,
+then the initialization should always use DECLARE_COMPLETION_ONSTACK()
+explicitly, not just to make lockdep happy, but also to make it clear
+that limited scope had been considered and is intentional::
+
+ DECLARE_COMPLETION_ONSTACK(setup_done)
+
+Note that when using completion objects as local variables you must be
+acutely aware of the short life time of the function stack: the function
+must not return to a calling context until all activities (such as waiting
+threads) have ceased and the completion object is completely unused.
+
+To emphasise this again: in particular when using some of the waiting API variants
+with more complex outcomes, such as the timeout or signalling (_timeout(),
+_killable() and _interruptible()) variants, the wait might complete
+prematurely while the object might still be in use by another thread - and a return
+from the wait_on_completion*() caller function will deallocate the function
+stack and cause subtle data corruption if a complete() is done in some
+other thread. Simple testing might not trigger these kinds of races.
+
+If unsure, use dynamically allocated completion objects, preferably embedded
+in some other long lived object that has a boringly long life time which
+exceeds the life time of any helper threads using the completion object,
+or has a lock or other synchronization mechanism to make sure complete()
+is not called on a freed object.
+
+A naive DECLARE_COMPLETION() on the stack triggers a lockdep warning.
+
+Waiting for completions:
+------------------------
+
+For a thread to wait for some concurrent activity to finish, it
+calls wait_for_completion() on the initialized completion structure::
+
+ void wait_for_completion(struct completion *done)
+
+A typical usage scenario is::
+
+ CPU#1 CPU#2
+
+ struct completion setup_done;
+
+ init_completion(&setup_done);
+ initialize_work(...,&setup_done,...);
+
+ /* run non-dependent code */ /* do setup */
+
+ wait_for_completion(&setup_done); complete(setup_done);
+
+This is not implying any particular order between wait_for_completion() and
+the call to complete() - if the call to complete() happened before the call
+to wait_for_completion() then the waiting side simply will continue
+immediately as all dependencies are satisfied; if not, it will block until
+completion is signaled by complete().
+
+Note that wait_for_completion() is calling spin_lock_irq()/spin_unlock_irq(),
+so it can only be called safely when you know that interrupts are enabled.
+Calling it from IRQs-off atomic contexts will result in hard-to-detect
+spurious enabling of interrupts.
+
+The default behavior is to wait without a timeout and to mark the task as
+uninterruptible. wait_for_completion() and its variants are only safe
+in process context (as they can sleep) but not in atomic context,
+interrupt context, with disabled IRQs, or preemption is disabled - see also
+try_wait_for_completion() below for handling completion in atomic/interrupt
+context.
+
+As all variants of wait_for_completion() can (obviously) block for a long
+time depending on the nature of the activity they are waiting for, so in
+most cases you probably don't want to call this with held mutexes.
+
+
+wait_for_completion*() variants available:
+------------------------------------------
+
+The below variants all return status and this status should be checked in
+most(/all) cases - in cases where the status is deliberately not checked you
+probably want to make a note explaining this (e.g. see
+arch/arm/kernel/smp.c:__cpu_up()).
+
+A common problem that occurs is to have unclean assignment of return types,
+so take care to assign return-values to variables of the proper type.
+
+Checking for the specific meaning of return values also has been found
+to be quite inaccurate, e.g. constructs like::
+
+ if (!wait_for_completion_interruptible_timeout(...))
+
+... would execute the same code path for successful completion and for the
+interrupted case - which is probably not what you want::
+
+ int wait_for_completion_interruptible(struct completion *done)
+
+This function marks the task TASK_INTERRUPTIBLE while it is waiting.
+If a signal was received while waiting it will return -ERESTARTSYS; 0 otherwise::
+
+ unsigned long wait_for_completion_timeout(struct completion *done, unsigned long timeout)
+
+The task is marked as TASK_UNINTERRUPTIBLE and will wait at most 'timeout'
+jiffies. If a timeout occurs it returns 0, else the remaining time in
+jiffies (but at least 1).
+
+Timeouts are preferably calculated with msecs_to_jiffies() or usecs_to_jiffies(),
+to make the code largely HZ-invariant.
+
+If the returned timeout value is deliberately ignored a comment should probably explain
+why (e.g. see drivers/mfd/wm8350-core.c wm8350_read_auxadc())::
+
+ long wait_for_completion_interruptible_timeout(struct completion *done, unsigned long timeout)
+
+This function passes a timeout in jiffies and marks the task as
+TASK_INTERRUPTIBLE. If a signal was received it will return -ERESTARTSYS;
+otherwise it returns 0 if the completion timed out, or the remaining time in
+jiffies if completion occurred.
+
+Further variants include _killable which uses TASK_KILLABLE as the
+designated tasks state and will return -ERESTARTSYS if it is interrupted,
+or 0 if completion was achieved. There is a _timeout variant as well::
+
+ long wait_for_completion_killable(struct completion *done)
+ long wait_for_completion_killable_timeout(struct completion *done, unsigned long timeout)
+
+The _io variants wait_for_completion_io() behave the same as the non-_io
+variants, except for accounting waiting time as 'waiting on IO', which has
+an impact on how the task is accounted in scheduling/IO stats::
+
+ void wait_for_completion_io(struct completion *done)
+ unsigned long wait_for_completion_io_timeout(struct completion *done, unsigned long timeout)
+
+
+Signaling completions:
+----------------------
+
+A thread that wants to signal that the conditions for continuation have been
+achieved calls complete() to signal exactly one of the waiters that it can
+continue::
+
+ void complete(struct completion *done)
+
+... or calls complete_all() to signal all current and future waiters::
+
+ void complete_all(struct completion *done)
+
+The signaling will work as expected even if completions are signaled before
+a thread starts waiting. This is achieved by the waiter "consuming"
+(decrementing) the done field of 'struct completion'. Waiting threads
+wakeup order is the same in which they were enqueued (FIFO order).
+
+If complete() is called multiple times then this will allow for that number
+of waiters to continue - each call to complete() will simply increment the
+done field. Calling complete_all() multiple times is a bug though. Both
+complete() and complete_all() can be called in IRQ/atomic context safely.
+
+There can only be one thread calling complete() or complete_all() on a
+particular 'struct completion' at any time - serialized through the wait
+queue spinlock. Any such concurrent calls to complete() or complete_all()
+probably are a design bug.
+
+Signaling completion from IRQ context is fine as it will appropriately
+lock with spin_lock_irqsave()/spin_unlock_irqrestore() and it will never
+sleep.
+
+
+try_wait_for_completion()/completion_done():
+--------------------------------------------
+
+The try_wait_for_completion() function will not put the thread on the wait
+queue but rather returns false if it would need to enqueue (block) the thread,
+else it consumes one posted completion and returns true::
+
+ bool try_wait_for_completion(struct completion *done)
+
+Finally, to check the state of a completion without changing it in any way,
+call completion_done(), which returns false if there are no posted
+completions that were not yet consumed by waiters (implying that there are
+waiters) and true otherwise::
+
+ bool completion_done(struct completion *done)
+
+Both try_wait_for_completion() and completion_done() are safe to be called in
+IRQ or atomic context.
+++ /dev/null
-Completions - "wait for completion" barrier APIs
-================================================
-
-Introduction:
--------------
-
-If you have one or more threads that must wait for some kernel activity
-to have reached a point or a specific state, completions can provide a
-race-free solution to this problem. Semantically they are somewhat like a
-pthread_barrier() and have similar use-cases.
-
-Completions are a code synchronization mechanism which is preferable to any
-misuse of locks/semaphores and busy-loops. Any time you think of using
-yield() or some quirky msleep(1) loop to allow something else to proceed,
-you probably want to look into using one of the wait_for_completion*()
-calls and complete() instead.
-
-The advantage of using completions is that they have a well defined, focused
-purpose which makes it very easy to see the intent of the code, but they
-also result in more efficient code as all threads can continue execution
-until the result is actually needed, and both the waiting and the signalling
-is highly efficient using low level scheduler sleep/wakeup facilities.
-
-Completions are built on top of the waitqueue and wakeup infrastructure of
-the Linux scheduler. The event the threads on the waitqueue are waiting for
-is reduced to a simple flag in 'struct completion', appropriately called "done".
-
-As completions are scheduling related, the code can be found in
-kernel/sched/completion.c.
-
-
-Usage:
-------
-
-There are three main parts to using completions:
-
- - the initialization of the 'struct completion' synchronization object
- - the waiting part through a call to one of the variants of wait_for_completion(),
- - the signaling side through a call to complete() or complete_all().
-
-There are also some helper functions for checking the state of completions.
-Note that while initialization must happen first, the waiting and signaling
-part can happen in any order. I.e. it's entirely normal for a thread
-to have marked a completion as 'done' before another thread checks whether
-it has to wait for it.
-
-To use completions you need to #include <linux/completion.h> and
-create a static or dynamic variable of type 'struct completion',
-which has only two fields:
-
- struct completion {
- unsigned int done;
- wait_queue_head_t wait;
- };
-
-This provides the ->wait waitqueue to place tasks on for waiting (if any), and
-the ->done completion flag for indicating whether it's completed or not.
-
-Completions should be named to refer to the event that is being synchronized on.
-A good example is:
-
- wait_for_completion(&early_console_added);
-
- complete(&early_console_added);
-
-Good, intuitive naming (as always) helps code readability. Naming a completion
-'complete' is not helpful unless the purpose is super obvious...
-
-
-Initializing completions:
--------------------------
-
-Dynamically allocated completion objects should preferably be embedded in data
-structures that are assured to be alive for the life-time of the function/driver,
-to prevent races with asynchronous complete() calls from occurring.
-
-Particular care should be taken when using the _timeout() or _killable()/_interruptible()
-variants of wait_for_completion(), as it must be assured that memory de-allocation
-does not happen until all related activities (complete() or reinit_completion())
-have taken place, even if these wait functions return prematurely due to a timeout
-or a signal triggering.
-
-Initializing of dynamically allocated completion objects is done via a call to
-init_completion():
-
- init_completion(&dynamic_object->done);
-
-In this call we initialize the waitqueue and set ->done to 0, i.e. "not completed"
-or "not done".
-
-The re-initialization function, reinit_completion(), simply resets the
-->done field to 0 ("not done"), without touching the waitqueue.
-Callers of this function must make sure that there are no racy
-wait_for_completion() calls going on in parallel.
-
-Calling init_completion() on the same completion object twice is
-most likely a bug as it re-initializes the queue to an empty queue and
-enqueued tasks could get "lost" - use reinit_completion() in that case,
-but be aware of other races.
-
-For static declaration and initialization, macros are available.
-
-For static (or global) declarations in file scope you can use DECLARE_COMPLETION():
-
- static DECLARE_COMPLETION(setup_done);
- DECLARE_COMPLETION(setup_done);
-
-Note that in this case the completion is boot time (or module load time)
-initialized to 'not done' and doesn't require an init_completion() call.
-
-When a completion is declared as a local variable within a function,
-then the initialization should always use DECLARE_COMPLETION_ONSTACK()
-explicitly, not just to make lockdep happy, but also to make it clear
-that limited scope had been considered and is intentional:
-
- DECLARE_COMPLETION_ONSTACK(setup_done)
-
-Note that when using completion objects as local variables you must be
-acutely aware of the short life time of the function stack: the function
-must not return to a calling context until all activities (such as waiting
-threads) have ceased and the completion object is completely unused.
-
-To emphasise this again: in particular when using some of the waiting API variants
-with more complex outcomes, such as the timeout or signalling (_timeout(),
-_killable() and _interruptible()) variants, the wait might complete
-prematurely while the object might still be in use by another thread - and a return
-from the wait_on_completion*() caller function will deallocate the function
-stack and cause subtle data corruption if a complete() is done in some
-other thread. Simple testing might not trigger these kinds of races.
-
-If unsure, use dynamically allocated completion objects, preferably embedded
-in some other long lived object that has a boringly long life time which
-exceeds the life time of any helper threads using the completion object,
-or has a lock or other synchronization mechanism to make sure complete()
-is not called on a freed object.
-
-A naive DECLARE_COMPLETION() on the stack triggers a lockdep warning.
-
-Waiting for completions:
-------------------------
-
-For a thread to wait for some concurrent activity to finish, it
-calls wait_for_completion() on the initialized completion structure:
-
- void wait_for_completion(struct completion *done)
-
-A typical usage scenario is:
-
- CPU#1 CPU#2
-
- struct completion setup_done;
-
- init_completion(&setup_done);
- initialize_work(...,&setup_done,...);
-
- /* run non-dependent code */ /* do setup */
-
- wait_for_completion(&setup_done); complete(setup_done);
-
-This is not implying any particular order between wait_for_completion() and
-the call to complete() - if the call to complete() happened before the call
-to wait_for_completion() then the waiting side simply will continue
-immediately as all dependencies are satisfied; if not, it will block until
-completion is signaled by complete().
-
-Note that wait_for_completion() is calling spin_lock_irq()/spin_unlock_irq(),
-so it can only be called safely when you know that interrupts are enabled.
-Calling it from IRQs-off atomic contexts will result in hard-to-detect
-spurious enabling of interrupts.
-
-The default behavior is to wait without a timeout and to mark the task as
-uninterruptible. wait_for_completion() and its variants are only safe
-in process context (as they can sleep) but not in atomic context,
-interrupt context, with disabled IRQs, or preemption is disabled - see also
-try_wait_for_completion() below for handling completion in atomic/interrupt
-context.
-
-As all variants of wait_for_completion() can (obviously) block for a long
-time depending on the nature of the activity they are waiting for, so in
-most cases you probably don't want to call this with held mutexes.
-
-
-wait_for_completion*() variants available:
-------------------------------------------
-
-The below variants all return status and this status should be checked in
-most(/all) cases - in cases where the status is deliberately not checked you
-probably want to make a note explaining this (e.g. see
-arch/arm/kernel/smp.c:__cpu_up()).
-
-A common problem that occurs is to have unclean assignment of return types,
-so take care to assign return-values to variables of the proper type.
-
-Checking for the specific meaning of return values also has been found
-to be quite inaccurate, e.g. constructs like:
-
- if (!wait_for_completion_interruptible_timeout(...))
-
-... would execute the same code path for successful completion and for the
-interrupted case - which is probably not what you want.
-
- int wait_for_completion_interruptible(struct completion *done)
-
-This function marks the task TASK_INTERRUPTIBLE while it is waiting.
-If a signal was received while waiting it will return -ERESTARTSYS; 0 otherwise.
-
- unsigned long wait_for_completion_timeout(struct completion *done, unsigned long timeout)
-
-The task is marked as TASK_UNINTERRUPTIBLE and will wait at most 'timeout'
-jiffies. If a timeout occurs it returns 0, else the remaining time in
-jiffies (but at least 1).
-
-Timeouts are preferably calculated with msecs_to_jiffies() or usecs_to_jiffies(),
-to make the code largely HZ-invariant.
-
-If the returned timeout value is deliberately ignored a comment should probably explain
-why (e.g. see drivers/mfd/wm8350-core.c wm8350_read_auxadc()).
-
- long wait_for_completion_interruptible_timeout(struct completion *done, unsigned long timeout)
-
-This function passes a timeout in jiffies and marks the task as
-TASK_INTERRUPTIBLE. If a signal was received it will return -ERESTARTSYS;
-otherwise it returns 0 if the completion timed out, or the remaining time in
-jiffies if completion occurred.
-
-Further variants include _killable which uses TASK_KILLABLE as the
-designated tasks state and will return -ERESTARTSYS if it is interrupted,
-or 0 if completion was achieved. There is a _timeout variant as well:
-
- long wait_for_completion_killable(struct completion *done)
- long wait_for_completion_killable_timeout(struct completion *done, unsigned long timeout)
-
-The _io variants wait_for_completion_io() behave the same as the non-_io
-variants, except for accounting waiting time as 'waiting on IO', which has
-an impact on how the task is accounted in scheduling/IO stats:
-
- void wait_for_completion_io(struct completion *done)
- unsigned long wait_for_completion_io_timeout(struct completion *done, unsigned long timeout)
-
-
-Signaling completions:
-----------------------
-
-A thread that wants to signal that the conditions for continuation have been
-achieved calls complete() to signal exactly one of the waiters that it can
-continue:
-
- void complete(struct completion *done)
-
-... or calls complete_all() to signal all current and future waiters:
-
- void complete_all(struct completion *done)
-
-The signaling will work as expected even if completions are signaled before
-a thread starts waiting. This is achieved by the waiter "consuming"
-(decrementing) the done field of 'struct completion'. Waiting threads
-wakeup order is the same in which they were enqueued (FIFO order).
-
-If complete() is called multiple times then this will allow for that number
-of waiters to continue - each call to complete() will simply increment the
-done field. Calling complete_all() multiple times is a bug though. Both
-complete() and complete_all() can be called in IRQ/atomic context safely.
-
-There can only be one thread calling complete() or complete_all() on a
-particular 'struct completion' at any time - serialized through the wait
-queue spinlock. Any such concurrent calls to complete() or complete_all()
-probably are a design bug.
-
-Signaling completion from IRQ context is fine as it will appropriately
-lock with spin_lock_irqsave()/spin_unlock_irqrestore() and it will never
-sleep.
-
-
-try_wait_for_completion()/completion_done():
---------------------------------------------
-
-The try_wait_for_completion() function will not put the thread on the wait
-queue but rather returns false if it would need to enqueue (block) the thread,
-else it consumes one posted completion and returns true.
-
- bool try_wait_for_completion(struct completion *done)
-
-Finally, to check the state of a completion without changing it in any way,
-call completion_done(), which returns false if there are no posted
-completions that were not yet consumed by waiters (implying that there are
-waiters) and true otherwise;
-
- bool completion_done(struct completion *done)
-
-Both try_wait_for_completion() and completion_done() are safe to be called in
-IRQ or atomic context.
--- /dev/null
+:orphan:
+
+===============
+Linux Scheduler
+===============
+
+.. toctree::
+ :maxdepth: 1
+
+
+ completion
+ sched-arch
+ sched-bwc
+ sched-deadline
+ sched-design-CFS
+ sched-domains
+ sched-energy
+ sched-nice-design
+ sched-rt-group
+ sched-stats
+
+ text_files
+
+.. only:: subproject and html
+
+ Indices
+ =======
+
+ * :ref:`genindex`
--- /dev/null
+=================================================================
+CPU Scheduler implementation hints for architecture specific code
+=================================================================
+
+ Nick Piggin, 2005
+
+Context switch
+==============
+1. Runqueue locking
+By default, the switch_to arch function is called with the runqueue
+locked. This is usually not a problem unless switch_to may need to
+take the runqueue lock. This is usually due to a wake up operation in
+the context switch. See arch/ia64/include/asm/switch_to.h for an example.
+
+To request the scheduler call switch_to with the runqueue unlocked,
+you must `#define __ARCH_WANT_UNLOCKED_CTXSW` in a header file
+(typically the one where switch_to is defined).
+
+Unlocked context switches introduce only a very minor performance
+penalty to the core scheduler implementation in the CONFIG_SMP case.
+
+CPU idle
+========
+Your cpu_idle routines need to obey the following rules:
+
+1. Preempt should now disabled over idle routines. Should only
+ be enabled to call schedule() then disabled again.
+
+2. need_resched/TIF_NEED_RESCHED is only ever set, and will never
+ be cleared until the running task has called schedule(). Idle
+ threads need only ever query need_resched, and may never set or
+ clear it.
+
+3. When cpu_idle finds (need_resched() == 'true'), it should call
+ schedule(). It should not call schedule() otherwise.
+
+4. The only time interrupts need to be disabled when checking
+ need_resched is if we are about to sleep the processor until
+ the next interrupt (this doesn't provide any protection of
+ need_resched, it prevents losing an interrupt):
+
+ 4a. Common problem with this type of sleep appears to be::
+
+ local_irq_disable();
+ if (!need_resched()) {
+ local_irq_enable();
+ *** resched interrupt arrives here ***
+ __asm__("sleep until next interrupt");
+ }
+
+5. TIF_POLLING_NRFLAG can be set by idle routines that do not
+ need an interrupt to wake them up when need_resched goes high.
+ In other words, they must be periodically polling need_resched,
+ although it may be reasonable to do some background work or enter
+ a low CPU priority.
+
+ - 5a. If TIF_POLLING_NRFLAG is set, and we do decide to enter
+ an interrupt sleep, it needs to be cleared then a memory
+ barrier issued (followed by a test of need_resched with
+ interrupts disabled, as explained in 3).
+
+arch/x86/kernel/process.c has examples of both polling and
+sleeping idle functions.
+
+
+Possible arch/ problems
+=======================
+
+Possible arch problems I found (and either tried to fix or didn't):
+
+ia64 - is safe_halt call racy vs interrupts? (does it sleep?) (See #4a)
+
+sh64 - Is sleeping racy vs interrupts? (See #4a)
+
+sparc - IRQs on at this point(?), change local_irq_save to _disable.
+ - TODO: needs secondary CPUs to disable preempt (See #1)
+++ /dev/null
- CPU Scheduler implementation hints for architecture specific code
-
- Nick Piggin, 2005
-
-Context switch
-==============
-1. Runqueue locking
-By default, the switch_to arch function is called with the runqueue
-locked. This is usually not a problem unless switch_to may need to
-take the runqueue lock. This is usually due to a wake up operation in
-the context switch. See arch/ia64/include/asm/switch_to.h for an example.
-
-To request the scheduler call switch_to with the runqueue unlocked,
-you must `#define __ARCH_WANT_UNLOCKED_CTXSW` in a header file
-(typically the one where switch_to is defined).
-
-Unlocked context switches introduce only a very minor performance
-penalty to the core scheduler implementation in the CONFIG_SMP case.
-
-CPU idle
-========
-Your cpu_idle routines need to obey the following rules:
-
-1. Preempt should now disabled over idle routines. Should only
- be enabled to call schedule() then disabled again.
-
-2. need_resched/TIF_NEED_RESCHED is only ever set, and will never
- be cleared until the running task has called schedule(). Idle
- threads need only ever query need_resched, and may never set or
- clear it.
-
-3. When cpu_idle finds (need_resched() == 'true'), it should call
- schedule(). It should not call schedule() otherwise.
-
-4. The only time interrupts need to be disabled when checking
- need_resched is if we are about to sleep the processor until
- the next interrupt (this doesn't provide any protection of
- need_resched, it prevents losing an interrupt).
-
- 4a. Common problem with this type of sleep appears to be:
- local_irq_disable();
- if (!need_resched()) {
- local_irq_enable();
- *** resched interrupt arrives here ***
- __asm__("sleep until next interrupt");
- }
-
-5. TIF_POLLING_NRFLAG can be set by idle routines that do not
- need an interrupt to wake them up when need_resched goes high.
- In other words, they must be periodically polling need_resched,
- although it may be reasonable to do some background work or enter
- a low CPU priority.
-
- 5a. If TIF_POLLING_NRFLAG is set, and we do decide to enter
- an interrupt sleep, it needs to be cleared then a memory
- barrier issued (followed by a test of need_resched with
- interrupts disabled, as explained in 3).
-
-arch/x86/kernel/process.c has examples of both polling and
-sleeping idle functions.
-
-
-Possible arch/ problems
-=======================
-
-Possible arch problems I found (and either tried to fix or didn't):
-
-ia64 - is safe_halt call racy vs interrupts? (does it sleep?) (See #4a)
-
-sh64 - Is sleeping racy vs interrupts? (See #4a)
-
-sparc - IRQs on at this point(?), change local_irq_save to _disable.
- - TODO: needs secondary CPUs to disable preempt (See #1)
-
--- /dev/null
+=====================
+CFS Bandwidth Control
+=====================
+
+[ This document only discusses CPU bandwidth control for SCHED_NORMAL.
+ The SCHED_RT case is covered in Documentation/scheduler/sched-rt-group.rst ]
+
+CFS bandwidth control is a CONFIG_FAIR_GROUP_SCHED extension which allows the
+specification of the maximum CPU bandwidth available to a group or hierarchy.
+
+The bandwidth allowed for a group is specified using a quota and period. Within
+each given "period" (microseconds), a group is allowed to consume only up to
+"quota" microseconds of CPU time. When the CPU bandwidth consumption of a
+group exceeds this limit (for that period), the tasks belonging to its
+hierarchy will be throttled and are not allowed to run again until the next
+period.
+
+A group's unused runtime is globally tracked, being refreshed with quota units
+above at each period boundary. As threads consume this bandwidth it is
+transferred to cpu-local "silos" on a demand basis. The amount transferred
+within each of these updates is tunable and described as the "slice".
+
+Management
+----------
+Quota and period are managed within the cpu subsystem via cgroupfs.
+
+cpu.cfs_quota_us: the total available run-time within a period (in microseconds)
+cpu.cfs_period_us: the length of a period (in microseconds)
+cpu.stat: exports throttling statistics [explained further below]
+
+The default values are::
+
+ cpu.cfs_period_us=100ms
+ cpu.cfs_quota=-1
+
+A value of -1 for cpu.cfs_quota_us indicates that the group does not have any
+bandwidth restriction in place, such a group is described as an unconstrained
+bandwidth group. This represents the traditional work-conserving behavior for
+CFS.
+
+Writing any (valid) positive value(s) will enact the specified bandwidth limit.
+The minimum quota allowed for the quota or period is 1ms. There is also an
+upper bound on the period length of 1s. Additional restrictions exist when
+bandwidth limits are used in a hierarchical fashion, these are explained in
+more detail below.
+
+Writing any negative value to cpu.cfs_quota_us will remove the bandwidth limit
+and return the group to an unconstrained state once more.
+
+Any updates to a group's bandwidth specification will result in it becoming
+unthrottled if it is in a constrained state.
+
+System wide settings
+--------------------
+For efficiency run-time is transferred between the global pool and CPU local
+"silos" in a batch fashion. This greatly reduces global accounting pressure
+on large systems. The amount transferred each time such an update is required
+is described as the "slice".
+
+This is tunable via procfs::
+
+ /proc/sys/kernel/sched_cfs_bandwidth_slice_us (default=5ms)
+
+Larger slice values will reduce transfer overheads, while smaller values allow
+for more fine-grained consumption.
+
+Statistics
+----------
+A group's bandwidth statistics are exported via 3 fields in cpu.stat.
+
+cpu.stat:
+
+- nr_periods: Number of enforcement intervals that have elapsed.
+- nr_throttled: Number of times the group has been throttled/limited.
+- throttled_time: The total time duration (in nanoseconds) for which entities
+ of the group have been throttled.
+
+This interface is read-only.
+
+Hierarchical considerations
+---------------------------
+The interface enforces that an individual entity's bandwidth is always
+attainable, that is: max(c_i) <= C. However, over-subscription in the
+aggregate case is explicitly allowed to enable work-conserving semantics
+within a hierarchy:
+
+ e.g. \Sum (c_i) may exceed C
+
+[ Where C is the parent's bandwidth, and c_i its children ]
+
+
+There are two ways in which a group may become throttled:
+
+ a. it fully consumes its own quota within a period
+ b. a parent's quota is fully consumed within its period
+
+In case b) above, even though the child may have runtime remaining it will not
+be allowed to until the parent's runtime is refreshed.
+
+Examples
+--------
+1. Limit a group to 1 CPU worth of runtime::
+
+ If period is 250ms and quota is also 250ms, the group will get
+ 1 CPU worth of runtime every 250ms.
+
+ # echo 250000 > cpu.cfs_quota_us /* quota = 250ms */
+ # echo 250000 > cpu.cfs_period_us /* period = 250ms */
+
+2. Limit a group to 2 CPUs worth of runtime on a multi-CPU machine
+
+ With 500ms period and 1000ms quota, the group can get 2 CPUs worth of
+ runtime every 500ms::
+
+ # echo 1000000 > cpu.cfs_quota_us /* quota = 1000ms */
+ # echo 500000 > cpu.cfs_period_us /* period = 500ms */
+
+ The larger period here allows for increased burst capacity.
+
+3. Limit a group to 20% of 1 CPU.
+
+ With 50ms period, 10ms quota will be equivalent to 20% of 1 CPU::
+
+ # echo 10000 > cpu.cfs_quota_us /* quota = 10ms */
+ # echo 50000 > cpu.cfs_period_us /* period = 50ms */
+
+ By using a small period here we are ensuring a consistent latency
+ response at the expense of burst capacity.
+++ /dev/null
-CFS Bandwidth Control
-=====================
-
-[ This document only discusses CPU bandwidth control for SCHED_NORMAL.
- The SCHED_RT case is covered in Documentation/scheduler/sched-rt-group.txt ]
-
-CFS bandwidth control is a CONFIG_FAIR_GROUP_SCHED extension which allows the
-specification of the maximum CPU bandwidth available to a group or hierarchy.
-
-The bandwidth allowed for a group is specified using a quota and period. Within
-each given "period" (microseconds), a group is allowed to consume only up to
-"quota" microseconds of CPU time. When the CPU bandwidth consumption of a
-group exceeds this limit (for that period), the tasks belonging to its
-hierarchy will be throttled and are not allowed to run again until the next
-period.
-
-A group's unused runtime is globally tracked, being refreshed with quota units
-above at each period boundary. As threads consume this bandwidth it is
-transferred to cpu-local "silos" on a demand basis. The amount transferred
-within each of these updates is tunable and described as the "slice".
-
-Management
-----------
-Quota and period are managed within the cpu subsystem via cgroupfs.
-
-cpu.cfs_quota_us: the total available run-time within a period (in microseconds)
-cpu.cfs_period_us: the length of a period (in microseconds)
-cpu.stat: exports throttling statistics [explained further below]
-
-The default values are:
- cpu.cfs_period_us=100ms
- cpu.cfs_quota=-1
-
-A value of -1 for cpu.cfs_quota_us indicates that the group does not have any
-bandwidth restriction in place, such a group is described as an unconstrained
-bandwidth group. This represents the traditional work-conserving behavior for
-CFS.
-
-Writing any (valid) positive value(s) will enact the specified bandwidth limit.
-The minimum quota allowed for the quota or period is 1ms. There is also an
-upper bound on the period length of 1s. Additional restrictions exist when
-bandwidth limits are used in a hierarchical fashion, these are explained in
-more detail below.
-
-Writing any negative value to cpu.cfs_quota_us will remove the bandwidth limit
-and return the group to an unconstrained state once more.
-
-Any updates to a group's bandwidth specification will result in it becoming
-unthrottled if it is in a constrained state.
-
-System wide settings
---------------------
-For efficiency run-time is transferred between the global pool and CPU local
-"silos" in a batch fashion. This greatly reduces global accounting pressure
-on large systems. The amount transferred each time such an update is required
-is described as the "slice".
-
-This is tunable via procfs:
- /proc/sys/kernel/sched_cfs_bandwidth_slice_us (default=5ms)
-
-Larger slice values will reduce transfer overheads, while smaller values allow
-for more fine-grained consumption.
-
-Statistics
-----------
-A group's bandwidth statistics are exported via 3 fields in cpu.stat.
-
-cpu.stat:
-- nr_periods: Number of enforcement intervals that have elapsed.
-- nr_throttled: Number of times the group has been throttled/limited.
-- throttled_time: The total time duration (in nanoseconds) for which entities
- of the group have been throttled.
-
-This interface is read-only.
-
-Hierarchical considerations
----------------------------
-The interface enforces that an individual entity's bandwidth is always
-attainable, that is: max(c_i) <= C. However, over-subscription in the
-aggregate case is explicitly allowed to enable work-conserving semantics
-within a hierarchy.
- e.g. \Sum (c_i) may exceed C
-[ Where C is the parent's bandwidth, and c_i its children ]
-
-
-There are two ways in which a group may become throttled:
- a. it fully consumes its own quota within a period
- b. a parent's quota is fully consumed within its period
-
-In case b) above, even though the child may have runtime remaining it will not
-be allowed to until the parent's runtime is refreshed.
-
-Examples
---------
-1. Limit a group to 1 CPU worth of runtime.
-
- If period is 250ms and quota is also 250ms, the group will get
- 1 CPU worth of runtime every 250ms.
-
- # echo 250000 > cpu.cfs_quota_us /* quota = 250ms */
- # echo 250000 > cpu.cfs_period_us /* period = 250ms */
-
-2. Limit a group to 2 CPUs worth of runtime on a multi-CPU machine.
-
- With 500ms period and 1000ms quota, the group can get 2 CPUs worth of
- runtime every 500ms.
-
- # echo 1000000 > cpu.cfs_quota_us /* quota = 1000ms */
- # echo 500000 > cpu.cfs_period_us /* period = 500ms */
-
- The larger period here allows for increased burst capacity.
-
-3. Limit a group to 20% of 1 CPU.
-
- With 50ms period, 10ms quota will be equivalent to 20% of 1 CPU.
-
- # echo 10000 > cpu.cfs_quota_us /* quota = 10ms */
- # echo 50000 > cpu.cfs_period_us /* period = 50ms */
-
- By using a small period here we are ensuring a consistent latency
- response at the expense of burst capacity.
-
--- /dev/null
+========================
+Deadline Task Scheduling
+========================
+
+.. CONTENTS
+
+ 0. WARNING
+ 1. Overview
+ 2. Scheduling algorithm
+ 2.1 Main algorithm
+ 2.2 Bandwidth reclaiming
+ 3. Scheduling Real-Time Tasks
+ 3.1 Definitions
+ 3.2 Schedulability Analysis for Uniprocessor Systems
+ 3.3 Schedulability Analysis for Multiprocessor Systems
+ 3.4 Relationship with SCHED_DEADLINE Parameters
+ 4. Bandwidth management
+ 4.1 System-wide settings
+ 4.2 Task interface
+ 4.3 Default behavior
+ 4.4 Behavior of sched_yield()
+ 5. Tasks CPU affinity
+ 5.1 SCHED_DEADLINE and cpusets HOWTO
+ 6. Future plans
+ A. Test suite
+ B. Minimal main()
+
+
+0. WARNING
+==========
+
+ Fiddling with these settings can result in an unpredictable or even unstable
+ system behavior. As for -rt (group) scheduling, it is assumed that root users
+ know what they're doing.
+
+
+1. Overview
+===========
+
+ The SCHED_DEADLINE policy contained inside the sched_dl scheduling class is
+ basically an implementation of the Earliest Deadline First (EDF) scheduling
+ algorithm, augmented with a mechanism (called Constant Bandwidth Server, CBS)
+ that makes it possible to isolate the behavior of tasks between each other.
+
+
+2. Scheduling algorithm
+=======================
+
+2.1 Main algorithm
+------------------
+
+ SCHED_DEADLINE [18] uses three parameters, named "runtime", "period", and
+ "deadline", to schedule tasks. A SCHED_DEADLINE task should receive
+ "runtime" microseconds of execution time every "period" microseconds, and
+ these "runtime" microseconds are available within "deadline" microseconds
+ from the beginning of the period. In order to implement this behavior,
+ every time the task wakes up, the scheduler computes a "scheduling deadline"
+ consistent with the guarantee (using the CBS[2,3] algorithm). Tasks are then
+ scheduled using EDF[1] on these scheduling deadlines (the task with the
+ earliest scheduling deadline is selected for execution). Notice that the
+ task actually receives "runtime" time units within "deadline" if a proper
+ "admission control" strategy (see Section "4. Bandwidth management") is used
+ (clearly, if the system is overloaded this guarantee cannot be respected).
+
+ Summing up, the CBS[2,3] algorithm assigns scheduling deadlines to tasks so
+ that each task runs for at most its runtime every period, avoiding any
+ interference between different tasks (bandwidth isolation), while the EDF[1]
+ algorithm selects the task with the earliest scheduling deadline as the one
+ to be executed next. Thanks to this feature, tasks that do not strictly comply
+ with the "traditional" real-time task model (see Section 3) can effectively
+ use the new policy.
+
+ In more details, the CBS algorithm assigns scheduling deadlines to
+ tasks in the following way:
+
+ - Each SCHED_DEADLINE task is characterized by the "runtime",
+ "deadline", and "period" parameters;
+
+ - The state of the task is described by a "scheduling deadline", and
+ a "remaining runtime". These two parameters are initially set to 0;
+
+ - When a SCHED_DEADLINE task wakes up (becomes ready for execution),
+ the scheduler checks if::
+
+ remaining runtime runtime
+ ---------------------------------- > ---------
+ scheduling deadline - current time period
+
+ then, if the scheduling deadline is smaller than the current time, or
+ this condition is verified, the scheduling deadline and the
+ remaining runtime are re-initialized as
+
+ scheduling deadline = current time + deadline
+ remaining runtime = runtime
+
+ otherwise, the scheduling deadline and the remaining runtime are
+ left unchanged;
+
+ - When a SCHED_DEADLINE task executes for an amount of time t, its
+ remaining runtime is decreased as::
+
+ remaining runtime = remaining runtime - t
+
+ (technically, the runtime is decreased at every tick, or when the
+ task is descheduled / preempted);
+
+ - When the remaining runtime becomes less or equal than 0, the task is
+ said to be "throttled" (also known as "depleted" in real-time literature)
+ and cannot be scheduled until its scheduling deadline. The "replenishment
+ time" for this task (see next item) is set to be equal to the current
+ value of the scheduling deadline;
+
+ - When the current time is equal to the replenishment time of a
+ throttled task, the scheduling deadline and the remaining runtime are
+ updated as::
+
+ scheduling deadline = scheduling deadline + period
+ remaining runtime = remaining runtime + runtime
+
+ The SCHED_FLAG_DL_OVERRUN flag in sched_attr's sched_flags field allows a task
+ to get informed about runtime overruns through the delivery of SIGXCPU
+ signals.
+
+
+2.2 Bandwidth reclaiming
+------------------------
+
+ Bandwidth reclaiming for deadline tasks is based on the GRUB (Greedy
+ Reclamation of Unused Bandwidth) algorithm [15, 16, 17] and it is enabled
+ when flag SCHED_FLAG_RECLAIM is set.
+
+ The following diagram illustrates the state names for tasks handled by GRUB::
+
+ ------------
+ (d) | Active |
+ ------------->| |
+ | | Contending |
+ | ------------
+ | A |
+ ---------- | |
+ | | | |
+ | Inactive | |(b) | (a)
+ | | | |
+ ---------- | |
+ A | V
+ | ------------
+ | | Active |
+ --------------| Non |
+ (c) | Contending |
+ ------------
+
+ A task can be in one of the following states:
+
+ - ActiveContending: if it is ready for execution (or executing);
+
+ - ActiveNonContending: if it just blocked and has not yet surpassed the 0-lag
+ time;
+
+ - Inactive: if it is blocked and has surpassed the 0-lag time.
+
+ State transitions:
+
+ (a) When a task blocks, it does not become immediately inactive since its
+ bandwidth cannot be immediately reclaimed without breaking the
+ real-time guarantees. It therefore enters a transitional state called
+ ActiveNonContending. The scheduler arms the "inactive timer" to fire at
+ the 0-lag time, when the task's bandwidth can be reclaimed without
+ breaking the real-time guarantees.
+
+ The 0-lag time for a task entering the ActiveNonContending state is
+ computed as::
+
+ (runtime * dl_period)
+ deadline - ---------------------
+ dl_runtime
+
+ where runtime is the remaining runtime, while dl_runtime and dl_period
+ are the reservation parameters.
+
+ (b) If the task wakes up before the inactive timer fires, the task re-enters
+ the ActiveContending state and the "inactive timer" is canceled.
+ In addition, if the task wakes up on a different runqueue, then
+ the task's utilization must be removed from the previous runqueue's active
+ utilization and must be added to the new runqueue's active utilization.
+ In order to avoid races between a task waking up on a runqueue while the
+ "inactive timer" is running on a different CPU, the "dl_non_contending"
+ flag is used to indicate that a task is not on a runqueue but is active
+ (so, the flag is set when the task blocks and is cleared when the
+ "inactive timer" fires or when the task wakes up).
+
+ (c) When the "inactive timer" fires, the task enters the Inactive state and
+ its utilization is removed from the runqueue's active utilization.
+
+ (d) When an inactive task wakes up, it enters the ActiveContending state and
+ its utilization is added to the active utilization of the runqueue where
+ it has been enqueued.
+
+ For each runqueue, the algorithm GRUB keeps track of two different bandwidths:
+
+ - Active bandwidth (running_bw): this is the sum of the bandwidths of all
+ tasks in active state (i.e., ActiveContending or ActiveNonContending);
+
+ - Total bandwidth (this_bw): this is the sum of all tasks "belonging" to the
+ runqueue, including the tasks in Inactive state.
+
+
+ The algorithm reclaims the bandwidth of the tasks in Inactive state.
+ It does so by decrementing the runtime of the executing task Ti at a pace equal
+ to
+
+ dq = -max{ Ui / Umax, (1 - Uinact - Uextra) } dt
+
+ where:
+
+ - Ui is the bandwidth of task Ti;
+ - Umax is the maximum reclaimable utilization (subjected to RT throttling
+ limits);
+ - Uinact is the (per runqueue) inactive utilization, computed as
+ (this_bq - running_bw);
+ - Uextra is the (per runqueue) extra reclaimable utilization
+ (subjected to RT throttling limits).
+
+
+ Let's now see a trivial example of two deadline tasks with runtime equal
+ to 4 and period equal to 8 (i.e., bandwidth equal to 0.5)::
+
+ A Task T1
+ |
+ | |
+ | |
+ |-------- |----
+ | | V
+ |---|---|---|---|---|---|---|---|--------->t
+ 0 1 2 3 4 5 6 7 8
+
+
+ A Task T2
+ |
+ | |
+ | |
+ | ------------------------|
+ | | V
+ |---|---|---|---|---|---|---|---|--------->t
+ 0 1 2 3 4 5 6 7 8
+
+
+ A running_bw
+ |
+ 1 ----------------- ------
+ | | |
+ 0.5- -----------------
+ | |
+ |---|---|---|---|---|---|---|---|--------->t
+ 0 1 2 3 4 5 6 7 8
+
+
+ - Time t = 0:
+
+ Both tasks are ready for execution and therefore in ActiveContending state.
+ Suppose Task T1 is the first task to start execution.
+ Since there are no inactive tasks, its runtime is decreased as dq = -1 dt.
+
+ - Time t = 2:
+
+ Suppose that task T1 blocks
+ Task T1 therefore enters the ActiveNonContending state. Since its remaining
+ runtime is equal to 2, its 0-lag time is equal to t = 4.
+ Task T2 start execution, with runtime still decreased as dq = -1 dt since
+ there are no inactive tasks.
+
+ - Time t = 4:
+
+ This is the 0-lag time for Task T1. Since it didn't woken up in the
+ meantime, it enters the Inactive state. Its bandwidth is removed from
+ running_bw.
+ Task T2 continues its execution. However, its runtime is now decreased as
+ dq = - 0.5 dt because Uinact = 0.5.
+ Task T2 therefore reclaims the bandwidth unused by Task T1.
+
+ - Time t = 8:
+
+ Task T1 wakes up. It enters the ActiveContending state again, and the
+ running_bw is incremented.
+
+
+2.3 Energy-aware scheduling
+---------------------------
+
+ When cpufreq's schedutil governor is selected, SCHED_DEADLINE implements the
+ GRUB-PA [19] algorithm, reducing the CPU operating frequency to the minimum
+ value that still allows to meet the deadlines. This behavior is currently
+ implemented only for ARM architectures.
+
+ A particular care must be taken in case the time needed for changing frequency
+ is of the same order of magnitude of the reservation period. In such cases,
+ setting a fixed CPU frequency results in a lower amount of deadline misses.
+
+
+3. Scheduling Real-Time Tasks
+=============================
+
+
+
+ .. BIG FAT WARNING ******************************************************
+
+ .. warning::
+
+ This section contains a (not-thorough) summary on classical deadline
+ scheduling theory, and how it applies to SCHED_DEADLINE.
+ The reader can "safely" skip to Section 4 if only interested in seeing
+ how the scheduling policy can be used. Anyway, we strongly recommend
+ to come back here and continue reading (once the urge for testing is
+ satisfied :P) to be sure of fully understanding all technical details.
+
+ .. ************************************************************************
+
+ There are no limitations on what kind of task can exploit this new
+ scheduling discipline, even if it must be said that it is particularly
+ suited for periodic or sporadic real-time tasks that need guarantees on their
+ timing behavior, e.g., multimedia, streaming, control applications, etc.
+
+3.1 Definitions
+------------------------
+
+ A typical real-time task is composed of a repetition of computation phases
+ (task instances, or jobs) which are activated on a periodic or sporadic
+ fashion.
+ Each job J_j (where J_j is the j^th job of the task) is characterized by an
+ arrival time r_j (the time when the job starts), an amount of computation
+ time c_j needed to finish the job, and a job absolute deadline d_j, which
+ is the time within which the job should be finished. The maximum execution
+ time max{c_j} is called "Worst Case Execution Time" (WCET) for the task.
+ A real-time task can be periodic with period P if r_{j+1} = r_j + P, or
+ sporadic with minimum inter-arrival time P is r_{j+1} >= r_j + P. Finally,
+ d_j = r_j + D, where D is the task's relative deadline.
+ Summing up, a real-time task can be described as
+
+ Task = (WCET, D, P)
+
+ The utilization of a real-time task is defined as the ratio between its
+ WCET and its period (or minimum inter-arrival time), and represents
+ the fraction of CPU time needed to execute the task.
+
+ If the total utilization U=sum(WCET_i/P_i) is larger than M (with M equal
+ to the number of CPUs), then the scheduler is unable to respect all the
+ deadlines.
+ Note that total utilization is defined as the sum of the utilizations
+ WCET_i/P_i over all the real-time tasks in the system. When considering
+ multiple real-time tasks, the parameters of the i-th task are indicated
+ with the "_i" suffix.
+ Moreover, if the total utilization is larger than M, then we risk starving
+ non- real-time tasks by real-time tasks.
+ If, instead, the total utilization is smaller than M, then non real-time
+ tasks will not be starved and the system might be able to respect all the
+ deadlines.
+ As a matter of fact, in this case it is possible to provide an upper bound
+ for tardiness (defined as the maximum between 0 and the difference
+ between the finishing time of a job and its absolute deadline).
+ More precisely, it can be proven that using a global EDF scheduler the
+ maximum tardiness of each task is smaller or equal than
+
+ ((M − 1) · WCET_max − WCET_min)/(M − (M − 2) · U_max) + WCET_max
+
+ where WCET_max = max{WCET_i} is the maximum WCET, WCET_min=min{WCET_i}
+ is the minimum WCET, and U_max = max{WCET_i/P_i} is the maximum
+ utilization[12].
+
+3.2 Schedulability Analysis for Uniprocessor Systems
+----------------------------------------------------
+
+ If M=1 (uniprocessor system), or in case of partitioned scheduling (each
+ real-time task is statically assigned to one and only one CPU), it is
+ possible to formally check if all the deadlines are respected.
+ If D_i = P_i for all tasks, then EDF is able to respect all the deadlines
+ of all the tasks executing on a CPU if and only if the total utilization
+ of the tasks running on such a CPU is smaller or equal than 1.
+ If D_i != P_i for some task, then it is possible to define the density of
+ a task as WCET_i/min{D_i,P_i}, and EDF is able to respect all the deadlines
+ of all the tasks running on a CPU if the sum of the densities of the tasks
+ running on such a CPU is smaller or equal than 1:
+
+ sum(WCET_i / min{D_i, P_i}) <= 1
+
+ It is important to notice that this condition is only sufficient, and not
+ necessary: there are task sets that are schedulable, but do not respect the
+ condition. For example, consider the task set {Task_1,Task_2} composed by
+ Task_1=(50ms,50ms,100ms) and Task_2=(10ms,100ms,100ms).
+ EDF is clearly able to schedule the two tasks without missing any deadline
+ (Task_1 is scheduled as soon as it is released, and finishes just in time
+ to respect its deadline; Task_2 is scheduled immediately after Task_1, hence
+ its response time cannot be larger than 50ms + 10ms = 60ms) even if
+
+ 50 / min{50,100} + 10 / min{100, 100} = 50 / 50 + 10 / 100 = 1.1
+
+ Of course it is possible to test the exact schedulability of tasks with
+ D_i != P_i (checking a condition that is both sufficient and necessary),
+ but this cannot be done by comparing the total utilization or density with
+ a constant. Instead, the so called "processor demand" approach can be used,
+ computing the total amount of CPU time h(t) needed by all the tasks to
+ respect all of their deadlines in a time interval of size t, and comparing
+ such a time with the interval size t. If h(t) is smaller than t (that is,
+ the amount of time needed by the tasks in a time interval of size t is
+ smaller than the size of the interval) for all the possible values of t, then
+ EDF is able to schedule the tasks respecting all of their deadlines. Since
+ performing this check for all possible values of t is impossible, it has been
+ proven[4,5,6] that it is sufficient to perform the test for values of t
+ between 0 and a maximum value L. The cited papers contain all of the
+ mathematical details and explain how to compute h(t) and L.
+ In any case, this kind of analysis is too complex as well as too
+ time-consuming to be performed on-line. Hence, as explained in Section
+ 4 Linux uses an admission test based on the tasks' utilizations.
+
+3.3 Schedulability Analysis for Multiprocessor Systems
+------------------------------------------------------
+
+ On multiprocessor systems with global EDF scheduling (non partitioned
+ systems), a sufficient test for schedulability can not be based on the
+ utilizations or densities: it can be shown that even if D_i = P_i task
+ sets with utilizations slightly larger than 1 can miss deadlines regardless
+ of the number of CPUs.
+
+ Consider a set {Task_1,...Task_{M+1}} of M+1 tasks on a system with M
+ CPUs, with the first task Task_1=(P,P,P) having period, relative deadline
+ and WCET equal to P. The remaining M tasks Task_i=(e,P-1,P-1) have an
+ arbitrarily small worst case execution time (indicated as "e" here) and a
+ period smaller than the one of the first task. Hence, if all the tasks
+ activate at the same time t, global EDF schedules these M tasks first
+ (because their absolute deadlines are equal to t + P - 1, hence they are
+ smaller than the absolute deadline of Task_1, which is t + P). As a
+ result, Task_1 can be scheduled only at time t + e, and will finish at
+ time t + e + P, after its absolute deadline. The total utilization of the
+ task set is U = M · e / (P - 1) + P / P = M · e / (P - 1) + 1, and for small
+ values of e this can become very close to 1. This is known as "Dhall's
+ effect"[7]. Note: the example in the original paper by Dhall has been
+ slightly simplified here (for example, Dhall more correctly computed
+ lim_{e->0}U).
+
+ More complex schedulability tests for global EDF have been developed in
+ real-time literature[8,9], but they are not based on a simple comparison
+ between total utilization (or density) and a fixed constant. If all tasks
+ have D_i = P_i, a sufficient schedulability condition can be expressed in
+ a simple way:
+
+ sum(WCET_i / P_i) <= M - (M - 1) · U_max
+
+ where U_max = max{WCET_i / P_i}[10]. Notice that for U_max = 1,
+ M - (M - 1) · U_max becomes M - M + 1 = 1 and this schedulability condition
+ just confirms the Dhall's effect. A more complete survey of the literature
+ about schedulability tests for multi-processor real-time scheduling can be
+ found in [11].
+
+ As seen, enforcing that the total utilization is smaller than M does not
+ guarantee that global EDF schedules the tasks without missing any deadline
+ (in other words, global EDF is not an optimal scheduling algorithm). However,
+ a total utilization smaller than M is enough to guarantee that non real-time
+ tasks are not starved and that the tardiness of real-time tasks has an upper
+ bound[12] (as previously noted). Different bounds on the maximum tardiness
+ experienced by real-time tasks have been developed in various papers[13,14],
+ but the theoretical result that is important for SCHED_DEADLINE is that if
+ the total utilization is smaller or equal than M then the response times of
+ the tasks are limited.
+
+3.4 Relationship with SCHED_DEADLINE Parameters
+-----------------------------------------------
+
+ Finally, it is important to understand the relationship between the
+ SCHED_DEADLINE scheduling parameters described in Section 2 (runtime,
+ deadline and period) and the real-time task parameters (WCET, D, P)
+ described in this section. Note that the tasks' temporal constraints are
+ represented by its absolute deadlines d_j = r_j + D described above, while
+ SCHED_DEADLINE schedules the tasks according to scheduling deadlines (see
+ Section 2).
+ If an admission test is used to guarantee that the scheduling deadlines
+ are respected, then SCHED_DEADLINE can be used to schedule real-time tasks
+ guaranteeing that all the jobs' deadlines of a task are respected.
+ In order to do this, a task must be scheduled by setting:
+
+ - runtime >= WCET
+ - deadline = D
+ - period <= P
+
+ IOW, if runtime >= WCET and if period is <= P, then the scheduling deadlines
+ and the absolute deadlines (d_j) coincide, so a proper admission control
+ allows to respect the jobs' absolute deadlines for this task (this is what is
+ called "hard schedulability property" and is an extension of Lemma 1 of [2]).
+ Notice that if runtime > deadline the admission control will surely reject
+ this task, as it is not possible to respect its temporal constraints.
+
+ References:
+
+ 1 - C. L. Liu and J. W. Layland. Scheduling algorithms for multiprogram-
+ ming in a hard-real-time environment. Journal of the Association for
+ Computing Machinery, 20(1), 1973.
+ 2 - L. Abeni , G. Buttazzo. Integrating Multimedia Applications in Hard
+ Real-Time Systems. Proceedings of the 19th IEEE Real-time Systems
+ Symposium, 1998. http://retis.sssup.it/~giorgio/paps/1998/rtss98-cbs.pdf
+ 3 - L. Abeni. Server Mechanisms for Multimedia Applications. ReTiS Lab
+ Technical Report. http://disi.unitn.it/~abeni/tr-98-01.pdf
+ 4 - J. Y. Leung and M.L. Merril. A Note on Preemptive Scheduling of
+ Periodic, Real-Time Tasks. Information Processing Letters, vol. 11,
+ no. 3, pp. 115-118, 1980.
+ 5 - S. K. Baruah, A. K. Mok and L. E. Rosier. Preemptively Scheduling
+ Hard-Real-Time Sporadic Tasks on One Processor. Proceedings of the
+ 11th IEEE Real-time Systems Symposium, 1990.
+ 6 - S. K. Baruah, L. E. Rosier and R. R. Howell. Algorithms and Complexity
+ Concerning the Preemptive Scheduling of Periodic Real-Time tasks on
+ One Processor. Real-Time Systems Journal, vol. 4, no. 2, pp 301-324,
+ 1990.
+ 7 - S. J. Dhall and C. L. Liu. On a real-time scheduling problem. Operations
+ research, vol. 26, no. 1, pp 127-140, 1978.
+ 8 - T. Baker. Multiprocessor EDF and Deadline Monotonic Schedulability
+ Analysis. Proceedings of the 24th IEEE Real-Time Systems Symposium, 2003.
+ 9 - T. Baker. An Analysis of EDF Schedulability on a Multiprocessor.
+ IEEE Transactions on Parallel and Distributed Systems, vol. 16, no. 8,
+ pp 760-768, 2005.
+ 10 - J. Goossens, S. Funk and S. Baruah, Priority-Driven Scheduling of
+ Periodic Task Systems on Multiprocessors. Real-Time Systems Journal,
+ vol. 25, no. 2–3, pp. 187–205, 2003.
+ 11 - R. Davis and A. Burns. A Survey of Hard Real-Time Scheduling for
+ Multiprocessor Systems. ACM Computing Surveys, vol. 43, no. 4, 2011.
+ http://www-users.cs.york.ac.uk/~robdavis/papers/MPSurveyv5.0.pdf
+ 12 - U. C. Devi and J. H. Anderson. Tardiness Bounds under Global EDF
+ Scheduling on a Multiprocessor. Real-Time Systems Journal, vol. 32,
+ no. 2, pp 133-189, 2008.
+ 13 - P. Valente and G. Lipari. An Upper Bound to the Lateness of Soft
+ Real-Time Tasks Scheduled by EDF on Multiprocessors. Proceedings of
+ the 26th IEEE Real-Time Systems Symposium, 2005.
+ 14 - J. Erickson, U. Devi and S. Baruah. Improved tardiness bounds for
+ Global EDF. Proceedings of the 22nd Euromicro Conference on
+ Real-Time Systems, 2010.
+ 15 - G. Lipari, S. Baruah, Greedy reclamation of unused bandwidth in
+ constant-bandwidth servers, 12th IEEE Euromicro Conference on Real-Time
+ Systems, 2000.
+ 16 - L. Abeni, J. Lelli, C. Scordino, L. Palopoli, Greedy CPU reclaiming for
+ SCHED DEADLINE. In Proceedings of the Real-Time Linux Workshop (RTLWS),
+ Dusseldorf, Germany, 2014.
+ 17 - L. Abeni, G. Lipari, A. Parri, Y. Sun, Multicore CPU reclaiming: parallel
+ or sequential?. In Proceedings of the 31st Annual ACM Symposium on Applied
+ Computing, 2016.
+ 18 - J. Lelli, C. Scordino, L. Abeni, D. Faggioli, Deadline scheduling in the
+ Linux kernel, Software: Practice and Experience, 46(6): 821-839, June
+ 2016.
+ 19 - C. Scordino, L. Abeni, J. Lelli, Energy-Aware Real-Time Scheduling in
+ the Linux Kernel, 33rd ACM/SIGAPP Symposium On Applied Computing (SAC
+ 2018), Pau, France, April 2018.
+
+
+4. Bandwidth management
+=======================
+
+ As previously mentioned, in order for -deadline scheduling to be
+ effective and useful (that is, to be able to provide "runtime" time units
+ within "deadline"), it is important to have some method to keep the allocation
+ of the available fractions of CPU time to the various tasks under control.
+ This is usually called "admission control" and if it is not performed, then
+ no guarantee can be given on the actual scheduling of the -deadline tasks.
+
+ As already stated in Section 3, a necessary condition to be respected to
+ correctly schedule a set of real-time tasks is that the total utilization
+ is smaller than M. When talking about -deadline tasks, this requires that
+ the sum of the ratio between runtime and period for all tasks is smaller
+ than M. Notice that the ratio runtime/period is equivalent to the utilization
+ of a "traditional" real-time task, and is also often referred to as
+ "bandwidth".
+ The interface used to control the CPU bandwidth that can be allocated
+ to -deadline tasks is similar to the one already used for -rt
+ tasks with real-time group scheduling (a.k.a. RT-throttling - see
+ Documentation/scheduler/sched-rt-group.rst), and is based on readable/
+ writable control files located in procfs (for system wide settings).
+ Notice that per-group settings (controlled through cgroupfs) are still not
+ defined for -deadline tasks, because more discussion is needed in order to
+ figure out how we want to manage SCHED_DEADLINE bandwidth at the task group
+ level.
+
+ A main difference between deadline bandwidth management and RT-throttling
+ is that -deadline tasks have bandwidth on their own (while -rt ones don't!),
+ and thus we don't need a higher level throttling mechanism to enforce the
+ desired bandwidth. In other words, this means that interface parameters are
+ only used at admission control time (i.e., when the user calls
+ sched_setattr()). Scheduling is then performed considering actual tasks'
+ parameters, so that CPU bandwidth is allocated to SCHED_DEADLINE tasks
+ respecting their needs in terms of granularity. Therefore, using this simple
+ interface we can put a cap on total utilization of -deadline tasks (i.e.,
+ \Sum (runtime_i / period_i) < global_dl_utilization_cap).
+
+4.1 System wide settings
+------------------------
+
+ The system wide settings are configured under the /proc virtual file system.
+
+ For now the -rt knobs are used for -deadline admission control and the
+ -deadline runtime is accounted against the -rt runtime. We realize that this
+ isn't entirely desirable; however, it is better to have a small interface for
+ now, and be able to change it easily later. The ideal situation (see 5.) is to
+ run -rt tasks from a -deadline server; in which case the -rt bandwidth is a
+ direct subset of dl_bw.
+
+ This means that, for a root_domain comprising M CPUs, -deadline tasks
+ can be created while the sum of their bandwidths stays below:
+
+ M * (sched_rt_runtime_us / sched_rt_period_us)
+
+ It is also possible to disable this bandwidth management logic, and
+ be thus free of oversubscribing the system up to any arbitrary level.
+ This is done by writing -1 in /proc/sys/kernel/sched_rt_runtime_us.
+
+
+4.2 Task interface
+------------------
+
+ Specifying a periodic/sporadic task that executes for a given amount of
+ runtime at each instance, and that is scheduled according to the urgency of
+ its own timing constraints needs, in general, a way of declaring:
+
+ - a (maximum/typical) instance execution time,
+ - a minimum interval between consecutive instances,
+ - a time constraint by which each instance must be completed.
+
+ Therefore:
+
+ * a new struct sched_attr, containing all the necessary fields is
+ provided;
+ * the new scheduling related syscalls that manipulate it, i.e.,
+ sched_setattr() and sched_getattr() are implemented.
+
+ For debugging purposes, the leftover runtime and absolute deadline of a
+ SCHED_DEADLINE task can be retrieved through /proc/<pid>/sched (entries
+ dl.runtime and dl.deadline, both values in ns). A programmatic way to
+ retrieve these values from production code is under discussion.
+
+
+4.3 Default behavior
+---------------------
+
+ The default value for SCHED_DEADLINE bandwidth is to have rt_runtime equal to
+ 950000. With rt_period equal to 1000000, by default, it means that -deadline
+ tasks can use at most 95%, multiplied by the number of CPUs that compose the
+ root_domain, for each root_domain.
+ This means that non -deadline tasks will receive at least 5% of the CPU time,
+ and that -deadline tasks will receive their runtime with a guaranteed
+ worst-case delay respect to the "deadline" parameter. If "deadline" = "period"
+ and the cpuset mechanism is used to implement partitioned scheduling (see
+ Section 5), then this simple setting of the bandwidth management is able to
+ deterministically guarantee that -deadline tasks will receive their runtime
+ in a period.
+
+ Finally, notice that in order not to jeopardize the admission control a
+ -deadline task cannot fork.
+
+
+4.4 Behavior of sched_yield()
+-----------------------------
+
+ When a SCHED_DEADLINE task calls sched_yield(), it gives up its
+ remaining runtime and is immediately throttled, until the next
+ period, when its runtime will be replenished (a special flag
+ dl_yielded is set and used to handle correctly throttling and runtime
+ replenishment after a call to sched_yield()).
+
+ This behavior of sched_yield() allows the task to wake-up exactly at
+ the beginning of the next period. Also, this may be useful in the
+ future with bandwidth reclaiming mechanisms, where sched_yield() will
+ make the leftoever runtime available for reclamation by other
+ SCHED_DEADLINE tasks.
+
+
+5. Tasks CPU affinity
+=====================
+
+ -deadline tasks cannot have an affinity mask smaller that the entire
+ root_domain they are created on. However, affinities can be specified
+ through the cpuset facility (Documentation/cgroup-v1/cpusets.txt).
+
+5.1 SCHED_DEADLINE and cpusets HOWTO
+------------------------------------
+
+ An example of a simple configuration (pin a -deadline task to CPU0)
+ follows (rt-app is used to create a -deadline task)::
+
+ mkdir /dev/cpuset
+ mount -t cgroup -o cpuset cpuset /dev/cpuset
+ cd /dev/cpuset
+ mkdir cpu0
+ echo 0 > cpu0/cpuset.cpus
+ echo 0 > cpu0/cpuset.mems
+ echo 1 > cpuset.cpu_exclusive
+ echo 0 > cpuset.sched_load_balance
+ echo 1 > cpu0/cpuset.cpu_exclusive
+ echo 1 > cpu0/cpuset.mem_exclusive
+ echo $$ > cpu0/tasks
+ rt-app -t 100000:10000:d:0 -D5 # it is now actually superfluous to specify
+ # task affinity
+
+6. Future plans
+===============
+
+ Still missing:
+
+ - programmatic way to retrieve current runtime and absolute deadline
+ - refinements to deadline inheritance, especially regarding the possibility
+ of retaining bandwidth isolation among non-interacting tasks. This is
+ being studied from both theoretical and practical points of view, and
+ hopefully we should be able to produce some demonstrative code soon;
+ - (c)group based bandwidth management, and maybe scheduling;
+ - access control for non-root users (and related security concerns to
+ address), which is the best way to allow unprivileged use of the mechanisms
+ and how to prevent non-root users "cheat" the system?
+
+ As already discussed, we are planning also to merge this work with the EDF
+ throttling patches [https://lkml.org/lkml/2010/2/23/239] but we still are in
+ the preliminary phases of the merge and we really seek feedback that would
+ help us decide on the direction it should take.
+
+Appendix A. Test suite
+======================
+
+ The SCHED_DEADLINE policy can be easily tested using two applications that
+ are part of a wider Linux Scheduler validation suite. The suite is
+ available as a GitHub repository: https://github.com/scheduler-tools.
+
+ The first testing application is called rt-app and can be used to
+ start multiple threads with specific parameters. rt-app supports
+ SCHED_{OTHER,FIFO,RR,DEADLINE} scheduling policies and their related
+ parameters (e.g., niceness, priority, runtime/deadline/period). rt-app
+ is a valuable tool, as it can be used to synthetically recreate certain
+ workloads (maybe mimicking real use-cases) and evaluate how the scheduler
+ behaves under such workloads. In this way, results are easily reproducible.
+ rt-app is available at: https://github.com/scheduler-tools/rt-app.
+
+ Thread parameters can be specified from the command line, with something like
+ this::
+
+ # rt-app -t 100000:10000:d -t 150000:20000:f:10 -D5
+
+ The above creates 2 threads. The first one, scheduled by SCHED_DEADLINE,
+ executes for 10ms every 100ms. The second one, scheduled at SCHED_FIFO
+ priority 10, executes for 20ms every 150ms. The test will run for a total
+ of 5 seconds.
+
+ More interestingly, configurations can be described with a json file that
+ can be passed as input to rt-app with something like this::
+
+ # rt-app my_config.json
+
+ The parameters that can be specified with the second method are a superset
+ of the command line options. Please refer to rt-app documentation for more
+ details (`<rt-app-sources>/doc/*.json`).
+
+ The second testing application is a modification of schedtool, called
+ schedtool-dl, which can be used to setup SCHED_DEADLINE parameters for a
+ certain pid/application. schedtool-dl is available at:
+ https://github.com/scheduler-tools/schedtool-dl.git.
+
+ The usage is straightforward::
+
+ # schedtool -E -t 10000000:100000000 -e ./my_cpuhog_app
+
+ With this, my_cpuhog_app is put to run inside a SCHED_DEADLINE reservation
+ of 10ms every 100ms (note that parameters are expressed in microseconds).
+ You can also use schedtool to create a reservation for an already running
+ application, given that you know its pid::
+
+ # schedtool -E -t 10000000:100000000 my_app_pid
+
+Appendix B. Minimal main()
+==========================
+
+ We provide in what follows a simple (ugly) self-contained code snippet
+ showing how SCHED_DEADLINE reservations can be created by a real-time
+ application developer::
+
+ #define _GNU_SOURCE
+ #include <unistd.h>
+ #include <stdio.h>
+ #include <stdlib.h>
+ #include <string.h>
+ #include <time.h>
+ #include <linux/unistd.h>
+ #include <linux/kernel.h>
+ #include <linux/types.h>
+ #include <sys/syscall.h>
+ #include <pthread.h>
+
+ #define gettid() syscall(__NR_gettid)
+
+ #define SCHED_DEADLINE 6
+
+ /* XXX use the proper syscall numbers */
+ #ifdef __x86_64__
+ #define __NR_sched_setattr 314
+ #define __NR_sched_getattr 315
+ #endif
+
+ #ifdef __i386__
+ #define __NR_sched_setattr 351
+ #define __NR_sched_getattr 352
+ #endif
+
+ #ifdef __arm__
+ #define __NR_sched_setattr 380
+ #define __NR_sched_getattr 381
+ #endif
+
+ static volatile int done;
+
+ struct sched_attr {
+ __u32 size;
+
+ __u32 sched_policy;
+ __u64 sched_flags;
+
+ /* SCHED_NORMAL, SCHED_BATCH */
+ __s32 sched_nice;
+
+ /* SCHED_FIFO, SCHED_RR */
+ __u32 sched_priority;
+
+ /* SCHED_DEADLINE (nsec) */
+ __u64 sched_runtime;
+ __u64 sched_deadline;
+ __u64 sched_period;
+ };
+
+ int sched_setattr(pid_t pid,
+ const struct sched_attr *attr,
+ unsigned int flags)
+ {
+ return syscall(__NR_sched_setattr, pid, attr, flags);
+ }
+
+ int sched_getattr(pid_t pid,
+ struct sched_attr *attr,
+ unsigned int size,
+ unsigned int flags)
+ {
+ return syscall(__NR_sched_getattr, pid, attr, size, flags);
+ }
+
+ void *run_deadline(void *data)
+ {
+ struct sched_attr attr;
+ int x = 0;
+ int ret;
+ unsigned int flags = 0;
+
+ printf("deadline thread started [%ld]\n", gettid());
+
+ attr.size = sizeof(attr);
+ attr.sched_flags = 0;
+ attr.sched_nice = 0;
+ attr.sched_priority = 0;
+
+ /* This creates a 10ms/30ms reservation */
+ attr.sched_policy = SCHED_DEADLINE;
+ attr.sched_runtime = 10 * 1000 * 1000;
+ attr.sched_period = attr.sched_deadline = 30 * 1000 * 1000;
+
+ ret = sched_setattr(0, &attr, flags);
+ if (ret < 0) {
+ done = 0;
+ perror("sched_setattr");
+ exit(-1);
+ }
+
+ while (!done) {
+ x++;
+ }
+
+ printf("deadline thread dies [%ld]\n", gettid());
+ return NULL;
+ }
+
+ int main (int argc, char **argv)
+ {
+ pthread_t thread;
+
+ printf("main thread [%ld]\n", gettid());
+
+ pthread_create(&thread, NULL, run_deadline, NULL);
+
+ sleep(10);
+
+ done = 1;
+ pthread_join(thread, NULL);
+
+ printf("main dies [%ld]\n", gettid());
+ return 0;
+ }
+++ /dev/null
- Deadline Task Scheduling
- ------------------------
-
-CONTENTS
-========
-
- 0. WARNING
- 1. Overview
- 2. Scheduling algorithm
- 2.1 Main algorithm
- 2.2 Bandwidth reclaiming
- 3. Scheduling Real-Time Tasks
- 3.1 Definitions
- 3.2 Schedulability Analysis for Uniprocessor Systems
- 3.3 Schedulability Analysis for Multiprocessor Systems
- 3.4 Relationship with SCHED_DEADLINE Parameters
- 4. Bandwidth management
- 4.1 System-wide settings
- 4.2 Task interface
- 4.3 Default behavior
- 4.4 Behavior of sched_yield()
- 5. Tasks CPU affinity
- 5.1 SCHED_DEADLINE and cpusets HOWTO
- 6. Future plans
- A. Test suite
- B. Minimal main()
-
-
-0. WARNING
-==========
-
- Fiddling with these settings can result in an unpredictable or even unstable
- system behavior. As for -rt (group) scheduling, it is assumed that root users
- know what they're doing.
-
-
-1. Overview
-===========
-
- The SCHED_DEADLINE policy contained inside the sched_dl scheduling class is
- basically an implementation of the Earliest Deadline First (EDF) scheduling
- algorithm, augmented with a mechanism (called Constant Bandwidth Server, CBS)
- that makes it possible to isolate the behavior of tasks between each other.
-
-
-2. Scheduling algorithm
-==================
-
-2.1 Main algorithm
-------------------
-
- SCHED_DEADLINE [18] uses three parameters, named "runtime", "period", and
- "deadline", to schedule tasks. A SCHED_DEADLINE task should receive
- "runtime" microseconds of execution time every "period" microseconds, and
- these "runtime" microseconds are available within "deadline" microseconds
- from the beginning of the period. In order to implement this behavior,
- every time the task wakes up, the scheduler computes a "scheduling deadline"
- consistent with the guarantee (using the CBS[2,3] algorithm). Tasks are then
- scheduled using EDF[1] on these scheduling deadlines (the task with the
- earliest scheduling deadline is selected for execution). Notice that the
- task actually receives "runtime" time units within "deadline" if a proper
- "admission control" strategy (see Section "4. Bandwidth management") is used
- (clearly, if the system is overloaded this guarantee cannot be respected).
-
- Summing up, the CBS[2,3] algorithm assigns scheduling deadlines to tasks so
- that each task runs for at most its runtime every period, avoiding any
- interference between different tasks (bandwidth isolation), while the EDF[1]
- algorithm selects the task with the earliest scheduling deadline as the one
- to be executed next. Thanks to this feature, tasks that do not strictly comply
- with the "traditional" real-time task model (see Section 3) can effectively
- use the new policy.
-
- In more details, the CBS algorithm assigns scheduling deadlines to
- tasks in the following way:
-
- - Each SCHED_DEADLINE task is characterized by the "runtime",
- "deadline", and "period" parameters;
-
- - The state of the task is described by a "scheduling deadline", and
- a "remaining runtime". These two parameters are initially set to 0;
-
- - When a SCHED_DEADLINE task wakes up (becomes ready for execution),
- the scheduler checks if
-
- remaining runtime runtime
- ---------------------------------- > ---------
- scheduling deadline - current time period
-
- then, if the scheduling deadline is smaller than the current time, or
- this condition is verified, the scheduling deadline and the
- remaining runtime are re-initialized as
-
- scheduling deadline = current time + deadline
- remaining runtime = runtime
-
- otherwise, the scheduling deadline and the remaining runtime are
- left unchanged;
-
- - When a SCHED_DEADLINE task executes for an amount of time t, its
- remaining runtime is decreased as
-
- remaining runtime = remaining runtime - t
-
- (technically, the runtime is decreased at every tick, or when the
- task is descheduled / preempted);
-
- - When the remaining runtime becomes less or equal than 0, the task is
- said to be "throttled" (also known as "depleted" in real-time literature)
- and cannot be scheduled until its scheduling deadline. The "replenishment
- time" for this task (see next item) is set to be equal to the current
- value of the scheduling deadline;
-
- - When the current time is equal to the replenishment time of a
- throttled task, the scheduling deadline and the remaining runtime are
- updated as
-
- scheduling deadline = scheduling deadline + period
- remaining runtime = remaining runtime + runtime
-
- The SCHED_FLAG_DL_OVERRUN flag in sched_attr's sched_flags field allows a task
- to get informed about runtime overruns through the delivery of SIGXCPU
- signals.
-
-
-2.2 Bandwidth reclaiming
-------------------------
-
- Bandwidth reclaiming for deadline tasks is based on the GRUB (Greedy
- Reclamation of Unused Bandwidth) algorithm [15, 16, 17] and it is enabled
- when flag SCHED_FLAG_RECLAIM is set.
-
- The following diagram illustrates the state names for tasks handled by GRUB:
-
- ------------
- (d) | Active |
- ------------->| |
- | | Contending |
- | ------------
- | A |
- ---------- | |
- | | | |
- | Inactive | |(b) | (a)
- | | | |
- ---------- | |
- A | V
- | ------------
- | | Active |
- --------------| Non |
- (c) | Contending |
- ------------
-
- A task can be in one of the following states:
-
- - ActiveContending: if it is ready for execution (or executing);
-
- - ActiveNonContending: if it just blocked and has not yet surpassed the 0-lag
- time;
-
- - Inactive: if it is blocked and has surpassed the 0-lag time.
-
- State transitions:
-
- (a) When a task blocks, it does not become immediately inactive since its
- bandwidth cannot be immediately reclaimed without breaking the
- real-time guarantees. It therefore enters a transitional state called
- ActiveNonContending. The scheduler arms the "inactive timer" to fire at
- the 0-lag time, when the task's bandwidth can be reclaimed without
- breaking the real-time guarantees.
-
- The 0-lag time for a task entering the ActiveNonContending state is
- computed as
-
- (runtime * dl_period)
- deadline - ---------------------
- dl_runtime
-
- where runtime is the remaining runtime, while dl_runtime and dl_period
- are the reservation parameters.
-
- (b) If the task wakes up before the inactive timer fires, the task re-enters
- the ActiveContending state and the "inactive timer" is canceled.
- In addition, if the task wakes up on a different runqueue, then
- the task's utilization must be removed from the previous runqueue's active
- utilization and must be added to the new runqueue's active utilization.
- In order to avoid races between a task waking up on a runqueue while the
- "inactive timer" is running on a different CPU, the "dl_non_contending"
- flag is used to indicate that a task is not on a runqueue but is active
- (so, the flag is set when the task blocks and is cleared when the
- "inactive timer" fires or when the task wakes up).
-
- (c) When the "inactive timer" fires, the task enters the Inactive state and
- its utilization is removed from the runqueue's active utilization.
-
- (d) When an inactive task wakes up, it enters the ActiveContending state and
- its utilization is added to the active utilization of the runqueue where
- it has been enqueued.
-
- For each runqueue, the algorithm GRUB keeps track of two different bandwidths:
-
- - Active bandwidth (running_bw): this is the sum of the bandwidths of all
- tasks in active state (i.e., ActiveContending or ActiveNonContending);
-
- - Total bandwidth (this_bw): this is the sum of all tasks "belonging" to the
- runqueue, including the tasks in Inactive state.
-
-
- The algorithm reclaims the bandwidth of the tasks in Inactive state.
- It does so by decrementing the runtime of the executing task Ti at a pace equal
- to
-
- dq = -max{ Ui / Umax, (1 - Uinact - Uextra) } dt
-
- where:
-
- - Ui is the bandwidth of task Ti;
- - Umax is the maximum reclaimable utilization (subjected to RT throttling
- limits);
- - Uinact is the (per runqueue) inactive utilization, computed as
- (this_bq - running_bw);
- - Uextra is the (per runqueue) extra reclaimable utilization
- (subjected to RT throttling limits).
-
-
- Let's now see a trivial example of two deadline tasks with runtime equal
- to 4 and period equal to 8 (i.e., bandwidth equal to 0.5):
-
- A Task T1
- |
- | |
- | |
- |-------- |----
- | | V
- |---|---|---|---|---|---|---|---|--------->t
- 0 1 2 3 4 5 6 7 8
-
-
- A Task T2
- |
- | |
- | |
- | ------------------------|
- | | V
- |---|---|---|---|---|---|---|---|--------->t
- 0 1 2 3 4 5 6 7 8
-
-
- A running_bw
- |
- 1 ----------------- ------
- | | |
- 0.5- -----------------
- | |
- |---|---|---|---|---|---|---|---|--------->t
- 0 1 2 3 4 5 6 7 8
-
-
- - Time t = 0:
-
- Both tasks are ready for execution and therefore in ActiveContending state.
- Suppose Task T1 is the first task to start execution.
- Since there are no inactive tasks, its runtime is decreased as dq = -1 dt.
-
- - Time t = 2:
-
- Suppose that task T1 blocks
- Task T1 therefore enters the ActiveNonContending state. Since its remaining
- runtime is equal to 2, its 0-lag time is equal to t = 4.
- Task T2 start execution, with runtime still decreased as dq = -1 dt since
- there are no inactive tasks.
-
- - Time t = 4:
-
- This is the 0-lag time for Task T1. Since it didn't woken up in the
- meantime, it enters the Inactive state. Its bandwidth is removed from
- running_bw.
- Task T2 continues its execution. However, its runtime is now decreased as
- dq = - 0.5 dt because Uinact = 0.5.
- Task T2 therefore reclaims the bandwidth unused by Task T1.
-
- - Time t = 8:
-
- Task T1 wakes up. It enters the ActiveContending state again, and the
- running_bw is incremented.
-
-
-2.3 Energy-aware scheduling
-------------------------
-
- When cpufreq's schedutil governor is selected, SCHED_DEADLINE implements the
- GRUB-PA [19] algorithm, reducing the CPU operating frequency to the minimum
- value that still allows to meet the deadlines. This behavior is currently
- implemented only for ARM architectures.
-
- A particular care must be taken in case the time needed for changing frequency
- is of the same order of magnitude of the reservation period. In such cases,
- setting a fixed CPU frequency results in a lower amount of deadline misses.
-
-
-3. Scheduling Real-Time Tasks
-=============================
-
- * BIG FAT WARNING ******************************************************
- *
- * This section contains a (not-thorough) summary on classical deadline
- * scheduling theory, and how it applies to SCHED_DEADLINE.
- * The reader can "safely" skip to Section 4 if only interested in seeing
- * how the scheduling policy can be used. Anyway, we strongly recommend
- * to come back here and continue reading (once the urge for testing is
- * satisfied :P) to be sure of fully understanding all technical details.
- ************************************************************************
-
- There are no limitations on what kind of task can exploit this new
- scheduling discipline, even if it must be said that it is particularly
- suited for periodic or sporadic real-time tasks that need guarantees on their
- timing behavior, e.g., multimedia, streaming, control applications, etc.
-
-3.1 Definitions
-------------------------
-
- A typical real-time task is composed of a repetition of computation phases
- (task instances, or jobs) which are activated on a periodic or sporadic
- fashion.
- Each job J_j (where J_j is the j^th job of the task) is characterized by an
- arrival time r_j (the time when the job starts), an amount of computation
- time c_j needed to finish the job, and a job absolute deadline d_j, which
- is the time within which the job should be finished. The maximum execution
- time max{c_j} is called "Worst Case Execution Time" (WCET) for the task.
- A real-time task can be periodic with period P if r_{j+1} = r_j + P, or
- sporadic with minimum inter-arrival time P is r_{j+1} >= r_j + P. Finally,
- d_j = r_j + D, where D is the task's relative deadline.
- Summing up, a real-time task can be described as
- Task = (WCET, D, P)
-
- The utilization of a real-time task is defined as the ratio between its
- WCET and its period (or minimum inter-arrival time), and represents
- the fraction of CPU time needed to execute the task.
-
- If the total utilization U=sum(WCET_i/P_i) is larger than M (with M equal
- to the number of CPUs), then the scheduler is unable to respect all the
- deadlines.
- Note that total utilization is defined as the sum of the utilizations
- WCET_i/P_i over all the real-time tasks in the system. When considering
- multiple real-time tasks, the parameters of the i-th task are indicated
- with the "_i" suffix.
- Moreover, if the total utilization is larger than M, then we risk starving
- non- real-time tasks by real-time tasks.
- If, instead, the total utilization is smaller than M, then non real-time
- tasks will not be starved and the system might be able to respect all the
- deadlines.
- As a matter of fact, in this case it is possible to provide an upper bound
- for tardiness (defined as the maximum between 0 and the difference
- between the finishing time of a job and its absolute deadline).
- More precisely, it can be proven that using a global EDF scheduler the
- maximum tardiness of each task is smaller or equal than
- ((M − 1) · WCET_max − WCET_min)/(M − (M − 2) · U_max) + WCET_max
- where WCET_max = max{WCET_i} is the maximum WCET, WCET_min=min{WCET_i}
- is the minimum WCET, and U_max = max{WCET_i/P_i} is the maximum
- utilization[12].
-
-3.2 Schedulability Analysis for Uniprocessor Systems
-------------------------
-
- If M=1 (uniprocessor system), or in case of partitioned scheduling (each
- real-time task is statically assigned to one and only one CPU), it is
- possible to formally check if all the deadlines are respected.
- If D_i = P_i for all tasks, then EDF is able to respect all the deadlines
- of all the tasks executing on a CPU if and only if the total utilization
- of the tasks running on such a CPU is smaller or equal than 1.
- If D_i != P_i for some task, then it is possible to define the density of
- a task as WCET_i/min{D_i,P_i}, and EDF is able to respect all the deadlines
- of all the tasks running on a CPU if the sum of the densities of the tasks
- running on such a CPU is smaller or equal than 1:
- sum(WCET_i / min{D_i, P_i}) <= 1
- It is important to notice that this condition is only sufficient, and not
- necessary: there are task sets that are schedulable, but do not respect the
- condition. For example, consider the task set {Task_1,Task_2} composed by
- Task_1=(50ms,50ms,100ms) and Task_2=(10ms,100ms,100ms).
- EDF is clearly able to schedule the two tasks without missing any deadline
- (Task_1 is scheduled as soon as it is released, and finishes just in time
- to respect its deadline; Task_2 is scheduled immediately after Task_1, hence
- its response time cannot be larger than 50ms + 10ms = 60ms) even if
- 50 / min{50,100} + 10 / min{100, 100} = 50 / 50 + 10 / 100 = 1.1
- Of course it is possible to test the exact schedulability of tasks with
- D_i != P_i (checking a condition that is both sufficient and necessary),
- but this cannot be done by comparing the total utilization or density with
- a constant. Instead, the so called "processor demand" approach can be used,
- computing the total amount of CPU time h(t) needed by all the tasks to
- respect all of their deadlines in a time interval of size t, and comparing
- such a time with the interval size t. If h(t) is smaller than t (that is,
- the amount of time needed by the tasks in a time interval of size t is
- smaller than the size of the interval) for all the possible values of t, then
- EDF is able to schedule the tasks respecting all of their deadlines. Since
- performing this check for all possible values of t is impossible, it has been
- proven[4,5,6] that it is sufficient to perform the test for values of t
- between 0 and a maximum value L. The cited papers contain all of the
- mathematical details and explain how to compute h(t) and L.
- In any case, this kind of analysis is too complex as well as too
- time-consuming to be performed on-line. Hence, as explained in Section
- 4 Linux uses an admission test based on the tasks' utilizations.
-
-3.3 Schedulability Analysis for Multiprocessor Systems
-------------------------
-
- On multiprocessor systems with global EDF scheduling (non partitioned
- systems), a sufficient test for schedulability can not be based on the
- utilizations or densities: it can be shown that even if D_i = P_i task
- sets with utilizations slightly larger than 1 can miss deadlines regardless
- of the number of CPUs.
-
- Consider a set {Task_1,...Task_{M+1}} of M+1 tasks on a system with M
- CPUs, with the first task Task_1=(P,P,P) having period, relative deadline
- and WCET equal to P. The remaining M tasks Task_i=(e,P-1,P-1) have an
- arbitrarily small worst case execution time (indicated as "e" here) and a
- period smaller than the one of the first task. Hence, if all the tasks
- activate at the same time t, global EDF schedules these M tasks first
- (because their absolute deadlines are equal to t + P - 1, hence they are
- smaller than the absolute deadline of Task_1, which is t + P). As a
- result, Task_1 can be scheduled only at time t + e, and will finish at
- time t + e + P, after its absolute deadline. The total utilization of the
- task set is U = M · e / (P - 1) + P / P = M · e / (P - 1) + 1, and for small
- values of e this can become very close to 1. This is known as "Dhall's
- effect"[7]. Note: the example in the original paper by Dhall has been
- slightly simplified here (for example, Dhall more correctly computed
- lim_{e->0}U).
-
- More complex schedulability tests for global EDF have been developed in
- real-time literature[8,9], but they are not based on a simple comparison
- between total utilization (or density) and a fixed constant. If all tasks
- have D_i = P_i, a sufficient schedulability condition can be expressed in
- a simple way:
- sum(WCET_i / P_i) <= M - (M - 1) · U_max
- where U_max = max{WCET_i / P_i}[10]. Notice that for U_max = 1,
- M - (M - 1) · U_max becomes M - M + 1 = 1 and this schedulability condition
- just confirms the Dhall's effect. A more complete survey of the literature
- about schedulability tests for multi-processor real-time scheduling can be
- found in [11].
-
- As seen, enforcing that the total utilization is smaller than M does not
- guarantee that global EDF schedules the tasks without missing any deadline
- (in other words, global EDF is not an optimal scheduling algorithm). However,
- a total utilization smaller than M is enough to guarantee that non real-time
- tasks are not starved and that the tardiness of real-time tasks has an upper
- bound[12] (as previously noted). Different bounds on the maximum tardiness
- experienced by real-time tasks have been developed in various papers[13,14],
- but the theoretical result that is important for SCHED_DEADLINE is that if
- the total utilization is smaller or equal than M then the response times of
- the tasks are limited.
-
-3.4 Relationship with SCHED_DEADLINE Parameters
-------------------------
-
- Finally, it is important to understand the relationship between the
- SCHED_DEADLINE scheduling parameters described in Section 2 (runtime,
- deadline and period) and the real-time task parameters (WCET, D, P)
- described in this section. Note that the tasks' temporal constraints are
- represented by its absolute deadlines d_j = r_j + D described above, while
- SCHED_DEADLINE schedules the tasks according to scheduling deadlines (see
- Section 2).
- If an admission test is used to guarantee that the scheduling deadlines
- are respected, then SCHED_DEADLINE can be used to schedule real-time tasks
- guaranteeing that all the jobs' deadlines of a task are respected.
- In order to do this, a task must be scheduled by setting:
-
- - runtime >= WCET
- - deadline = D
- - period <= P
-
- IOW, if runtime >= WCET and if period is <= P, then the scheduling deadlines
- and the absolute deadlines (d_j) coincide, so a proper admission control
- allows to respect the jobs' absolute deadlines for this task (this is what is
- called "hard schedulability property" and is an extension of Lemma 1 of [2]).
- Notice that if runtime > deadline the admission control will surely reject
- this task, as it is not possible to respect its temporal constraints.
-
- References:
- 1 - C. L. Liu and J. W. Layland. Scheduling algorithms for multiprogram-
- ming in a hard-real-time environment. Journal of the Association for
- Computing Machinery, 20(1), 1973.
- 2 - L. Abeni , G. Buttazzo. Integrating Multimedia Applications in Hard
- Real-Time Systems. Proceedings of the 19th IEEE Real-time Systems
- Symposium, 1998. http://retis.sssup.it/~giorgio/paps/1998/rtss98-cbs.pdf
- 3 - L. Abeni. Server Mechanisms for Multimedia Applications. ReTiS Lab
- Technical Report. http://disi.unitn.it/~abeni/tr-98-01.pdf
- 4 - J. Y. Leung and M.L. Merril. A Note on Preemptive Scheduling of
- Periodic, Real-Time Tasks. Information Processing Letters, vol. 11,
- no. 3, pp. 115-118, 1980.
- 5 - S. K. Baruah, A. K. Mok and L. E. Rosier. Preemptively Scheduling
- Hard-Real-Time Sporadic Tasks on One Processor. Proceedings of the
- 11th IEEE Real-time Systems Symposium, 1990.
- 6 - S. K. Baruah, L. E. Rosier and R. R. Howell. Algorithms and Complexity
- Concerning the Preemptive Scheduling of Periodic Real-Time tasks on
- One Processor. Real-Time Systems Journal, vol. 4, no. 2, pp 301-324,
- 1990.
- 7 - S. J. Dhall and C. L. Liu. On a real-time scheduling problem. Operations
- research, vol. 26, no. 1, pp 127-140, 1978.
- 8 - T. Baker. Multiprocessor EDF and Deadline Monotonic Schedulability
- Analysis. Proceedings of the 24th IEEE Real-Time Systems Symposium, 2003.
- 9 - T. Baker. An Analysis of EDF Schedulability on a Multiprocessor.
- IEEE Transactions on Parallel and Distributed Systems, vol. 16, no. 8,
- pp 760-768, 2005.
- 10 - J. Goossens, S. Funk and S. Baruah, Priority-Driven Scheduling of
- Periodic Task Systems on Multiprocessors. Real-Time Systems Journal,
- vol. 25, no. 2–3, pp. 187–205, 2003.
- 11 - R. Davis and A. Burns. A Survey of Hard Real-Time Scheduling for
- Multiprocessor Systems. ACM Computing Surveys, vol. 43, no. 4, 2011.
- http://www-users.cs.york.ac.uk/~robdavis/papers/MPSurveyv5.0.pdf
- 12 - U. C. Devi and J. H. Anderson. Tardiness Bounds under Global EDF
- Scheduling on a Multiprocessor. Real-Time Systems Journal, vol. 32,
- no. 2, pp 133-189, 2008.
- 13 - P. Valente and G. Lipari. An Upper Bound to the Lateness of Soft
- Real-Time Tasks Scheduled by EDF on Multiprocessors. Proceedings of
- the 26th IEEE Real-Time Systems Symposium, 2005.
- 14 - J. Erickson, U. Devi and S. Baruah. Improved tardiness bounds for
- Global EDF. Proceedings of the 22nd Euromicro Conference on
- Real-Time Systems, 2010.
- 15 - G. Lipari, S. Baruah, Greedy reclamation of unused bandwidth in
- constant-bandwidth servers, 12th IEEE Euromicro Conference on Real-Time
- Systems, 2000.
- 16 - L. Abeni, J. Lelli, C. Scordino, L. Palopoli, Greedy CPU reclaiming for
- SCHED DEADLINE. In Proceedings of the Real-Time Linux Workshop (RTLWS),
- Dusseldorf, Germany, 2014.
- 17 - L. Abeni, G. Lipari, A. Parri, Y. Sun, Multicore CPU reclaiming: parallel
- or sequential?. In Proceedings of the 31st Annual ACM Symposium on Applied
- Computing, 2016.
- 18 - J. Lelli, C. Scordino, L. Abeni, D. Faggioli, Deadline scheduling in the
- Linux kernel, Software: Practice and Experience, 46(6): 821-839, June
- 2016.
- 19 - C. Scordino, L. Abeni, J. Lelli, Energy-Aware Real-Time Scheduling in
- the Linux Kernel, 33rd ACM/SIGAPP Symposium On Applied Computing (SAC
- 2018), Pau, France, April 2018.
-
-
-4. Bandwidth management
-=======================
-
- As previously mentioned, in order for -deadline scheduling to be
- effective and useful (that is, to be able to provide "runtime" time units
- within "deadline"), it is important to have some method to keep the allocation
- of the available fractions of CPU time to the various tasks under control.
- This is usually called "admission control" and if it is not performed, then
- no guarantee can be given on the actual scheduling of the -deadline tasks.
-
- As already stated in Section 3, a necessary condition to be respected to
- correctly schedule a set of real-time tasks is that the total utilization
- is smaller than M. When talking about -deadline tasks, this requires that
- the sum of the ratio between runtime and period for all tasks is smaller
- than M. Notice that the ratio runtime/period is equivalent to the utilization
- of a "traditional" real-time task, and is also often referred to as
- "bandwidth".
- The interface used to control the CPU bandwidth that can be allocated
- to -deadline tasks is similar to the one already used for -rt
- tasks with real-time group scheduling (a.k.a. RT-throttling - see
- Documentation/scheduler/sched-rt-group.txt), and is based on readable/
- writable control files located in procfs (for system wide settings).
- Notice that per-group settings (controlled through cgroupfs) are still not
- defined for -deadline tasks, because more discussion is needed in order to
- figure out how we want to manage SCHED_DEADLINE bandwidth at the task group
- level.
-
- A main difference between deadline bandwidth management and RT-throttling
- is that -deadline tasks have bandwidth on their own (while -rt ones don't!),
- and thus we don't need a higher level throttling mechanism to enforce the
- desired bandwidth. In other words, this means that interface parameters are
- only used at admission control time (i.e., when the user calls
- sched_setattr()). Scheduling is then performed considering actual tasks'
- parameters, so that CPU bandwidth is allocated to SCHED_DEADLINE tasks
- respecting their needs in terms of granularity. Therefore, using this simple
- interface we can put a cap on total utilization of -deadline tasks (i.e.,
- \Sum (runtime_i / period_i) < global_dl_utilization_cap).
-
-4.1 System wide settings
-------------------------
-
- The system wide settings are configured under the /proc virtual file system.
-
- For now the -rt knobs are used for -deadline admission control and the
- -deadline runtime is accounted against the -rt runtime. We realize that this
- isn't entirely desirable; however, it is better to have a small interface for
- now, and be able to change it easily later. The ideal situation (see 5.) is to
- run -rt tasks from a -deadline server; in which case the -rt bandwidth is a
- direct subset of dl_bw.
-
- This means that, for a root_domain comprising M CPUs, -deadline tasks
- can be created while the sum of their bandwidths stays below:
-
- M * (sched_rt_runtime_us / sched_rt_period_us)
-
- It is also possible to disable this bandwidth management logic, and
- be thus free of oversubscribing the system up to any arbitrary level.
- This is done by writing -1 in /proc/sys/kernel/sched_rt_runtime_us.
-
-
-4.2 Task interface
-------------------
-
- Specifying a periodic/sporadic task that executes for a given amount of
- runtime at each instance, and that is scheduled according to the urgency of
- its own timing constraints needs, in general, a way of declaring:
- - a (maximum/typical) instance execution time,
- - a minimum interval between consecutive instances,
- - a time constraint by which each instance must be completed.
-
- Therefore:
- * a new struct sched_attr, containing all the necessary fields is
- provided;
- * the new scheduling related syscalls that manipulate it, i.e.,
- sched_setattr() and sched_getattr() are implemented.
-
- For debugging purposes, the leftover runtime and absolute deadline of a
- SCHED_DEADLINE task can be retrieved through /proc/<pid>/sched (entries
- dl.runtime and dl.deadline, both values in ns). A programmatic way to
- retrieve these values from production code is under discussion.
-
-
-4.3 Default behavior
----------------------
-
- The default value for SCHED_DEADLINE bandwidth is to have rt_runtime equal to
- 950000. With rt_period equal to 1000000, by default, it means that -deadline
- tasks can use at most 95%, multiplied by the number of CPUs that compose the
- root_domain, for each root_domain.
- This means that non -deadline tasks will receive at least 5% of the CPU time,
- and that -deadline tasks will receive their runtime with a guaranteed
- worst-case delay respect to the "deadline" parameter. If "deadline" = "period"
- and the cpuset mechanism is used to implement partitioned scheduling (see
- Section 5), then this simple setting of the bandwidth management is able to
- deterministically guarantee that -deadline tasks will receive their runtime
- in a period.
-
- Finally, notice that in order not to jeopardize the admission control a
- -deadline task cannot fork.
-
-
-4.4 Behavior of sched_yield()
------------------------------
-
- When a SCHED_DEADLINE task calls sched_yield(), it gives up its
- remaining runtime and is immediately throttled, until the next
- period, when its runtime will be replenished (a special flag
- dl_yielded is set and used to handle correctly throttling and runtime
- replenishment after a call to sched_yield()).
-
- This behavior of sched_yield() allows the task to wake-up exactly at
- the beginning of the next period. Also, this may be useful in the
- future with bandwidth reclaiming mechanisms, where sched_yield() will
- make the leftoever runtime available for reclamation by other
- SCHED_DEADLINE tasks.
-
-
-5. Tasks CPU affinity
-=====================
-
- -deadline tasks cannot have an affinity mask smaller that the entire
- root_domain they are created on. However, affinities can be specified
- through the cpuset facility (Documentation/cgroup-v1/cpusets.txt).
-
-5.1 SCHED_DEADLINE and cpusets HOWTO
-------------------------------------
-
- An example of a simple configuration (pin a -deadline task to CPU0)
- follows (rt-app is used to create a -deadline task).
-
- mkdir /dev/cpuset
- mount -t cgroup -o cpuset cpuset /dev/cpuset
- cd /dev/cpuset
- mkdir cpu0
- echo 0 > cpu0/cpuset.cpus
- echo 0 > cpu0/cpuset.mems
- echo 1 > cpuset.cpu_exclusive
- echo 0 > cpuset.sched_load_balance
- echo 1 > cpu0/cpuset.cpu_exclusive
- echo 1 > cpu0/cpuset.mem_exclusive
- echo $$ > cpu0/tasks
- rt-app -t 100000:10000:d:0 -D5 (it is now actually superfluous to specify
- task affinity)
-
-6. Future plans
-===============
-
- Still missing:
-
- - programmatic way to retrieve current runtime and absolute deadline
- - refinements to deadline inheritance, especially regarding the possibility
- of retaining bandwidth isolation among non-interacting tasks. This is
- being studied from both theoretical and practical points of view, and
- hopefully we should be able to produce some demonstrative code soon;
- - (c)group based bandwidth management, and maybe scheduling;
- - access control for non-root users (and related security concerns to
- address), which is the best way to allow unprivileged use of the mechanisms
- and how to prevent non-root users "cheat" the system?
-
- As already discussed, we are planning also to merge this work with the EDF
- throttling patches [https://lkml.org/lkml/2010/2/23/239] but we still are in
- the preliminary phases of the merge and we really seek feedback that would
- help us decide on the direction it should take.
-
-Appendix A. Test suite
-======================
-
- The SCHED_DEADLINE policy can be easily tested using two applications that
- are part of a wider Linux Scheduler validation suite. The suite is
- available as a GitHub repository: https://github.com/scheduler-tools.
-
- The first testing application is called rt-app and can be used to
- start multiple threads with specific parameters. rt-app supports
- SCHED_{OTHER,FIFO,RR,DEADLINE} scheduling policies and their related
- parameters (e.g., niceness, priority, runtime/deadline/period). rt-app
- is a valuable tool, as it can be used to synthetically recreate certain
- workloads (maybe mimicking real use-cases) and evaluate how the scheduler
- behaves under such workloads. In this way, results are easily reproducible.
- rt-app is available at: https://github.com/scheduler-tools/rt-app.
-
- Thread parameters can be specified from the command line, with something like
- this:
-
- # rt-app -t 100000:10000:d -t 150000:20000:f:10 -D5
-
- The above creates 2 threads. The first one, scheduled by SCHED_DEADLINE,
- executes for 10ms every 100ms. The second one, scheduled at SCHED_FIFO
- priority 10, executes for 20ms every 150ms. The test will run for a total
- of 5 seconds.
-
- More interestingly, configurations can be described with a json file that
- can be passed as input to rt-app with something like this:
-
- # rt-app my_config.json
-
- The parameters that can be specified with the second method are a superset
- of the command line options. Please refer to rt-app documentation for more
- details (<rt-app-sources>/doc/*.json).
-
- The second testing application is a modification of schedtool, called
- schedtool-dl, which can be used to setup SCHED_DEADLINE parameters for a
- certain pid/application. schedtool-dl is available at:
- https://github.com/scheduler-tools/schedtool-dl.git.
-
- The usage is straightforward:
-
- # schedtool -E -t 10000000:100000000 -e ./my_cpuhog_app
-
- With this, my_cpuhog_app is put to run inside a SCHED_DEADLINE reservation
- of 10ms every 100ms (note that parameters are expressed in microseconds).
- You can also use schedtool to create a reservation for an already running
- application, given that you know its pid:
-
- # schedtool -E -t 10000000:100000000 my_app_pid
-
-Appendix B. Minimal main()
-==========================
-
- We provide in what follows a simple (ugly) self-contained code snippet
- showing how SCHED_DEADLINE reservations can be created by a real-time
- application developer.
-
- #define _GNU_SOURCE
- #include <unistd.h>
- #include <stdio.h>
- #include <stdlib.h>
- #include <string.h>
- #include <time.h>
- #include <linux/unistd.h>
- #include <linux/kernel.h>
- #include <linux/types.h>
- #include <sys/syscall.h>
- #include <pthread.h>
-
- #define gettid() syscall(__NR_gettid)
-
- #define SCHED_DEADLINE 6
-
- /* XXX use the proper syscall numbers */
- #ifdef __x86_64__
- #define __NR_sched_setattr 314
- #define __NR_sched_getattr 315
- #endif
-
- #ifdef __i386__
- #define __NR_sched_setattr 351
- #define __NR_sched_getattr 352
- #endif
-
- #ifdef __arm__
- #define __NR_sched_setattr 380
- #define __NR_sched_getattr 381
- #endif
-
- static volatile int done;
-
- struct sched_attr {
- __u32 size;
-
- __u32 sched_policy;
- __u64 sched_flags;
-
- /* SCHED_NORMAL, SCHED_BATCH */
- __s32 sched_nice;
-
- /* SCHED_FIFO, SCHED_RR */
- __u32 sched_priority;
-
- /* SCHED_DEADLINE (nsec) */
- __u64 sched_runtime;
- __u64 sched_deadline;
- __u64 sched_period;
- };
-
- int sched_setattr(pid_t pid,
- const struct sched_attr *attr,
- unsigned int flags)
- {
- return syscall(__NR_sched_setattr, pid, attr, flags);
- }
-
- int sched_getattr(pid_t pid,
- struct sched_attr *attr,
- unsigned int size,
- unsigned int flags)
- {
- return syscall(__NR_sched_getattr, pid, attr, size, flags);
- }
-
- void *run_deadline(void *data)
- {
- struct sched_attr attr;
- int x = 0;
- int ret;
- unsigned int flags = 0;
-
- printf("deadline thread started [%ld]\n", gettid());
-
- attr.size = sizeof(attr);
- attr.sched_flags = 0;
- attr.sched_nice = 0;
- attr.sched_priority = 0;
-
- /* This creates a 10ms/30ms reservation */
- attr.sched_policy = SCHED_DEADLINE;
- attr.sched_runtime = 10 * 1000 * 1000;
- attr.sched_period = attr.sched_deadline = 30 * 1000 * 1000;
-
- ret = sched_setattr(0, &attr, flags);
- if (ret < 0) {
- done = 0;
- perror("sched_setattr");
- exit(-1);
- }
-
- while (!done) {
- x++;
- }
-
- printf("deadline thread dies [%ld]\n", gettid());
- return NULL;
- }
-
- int main (int argc, char **argv)
- {
- pthread_t thread;
-
- printf("main thread [%ld]\n", gettid());
-
- pthread_create(&thread, NULL, run_deadline, NULL);
-
- sleep(10);
-
- done = 1;
- pthread_join(thread, NULL);
-
- printf("main dies [%ld]\n", gettid());
- return 0;
- }
--- /dev/null
+=============
+CFS Scheduler
+=============
+
+
+1. OVERVIEW
+============
+
+CFS stands for "Completely Fair Scheduler," and is the new "desktop" process
+scheduler implemented by Ingo Molnar and merged in Linux 2.6.23. It is the
+replacement for the previous vanilla scheduler's SCHED_OTHER interactivity
+code.
+
+80% of CFS's design can be summed up in a single sentence: CFS basically models
+an "ideal, precise multi-tasking CPU" on real hardware.
+
+"Ideal multi-tasking CPU" is a (non-existent :-)) CPU that has 100% physical
+power and which can run each task at precise equal speed, in parallel, each at
+1/nr_running speed. For example: if there are 2 tasks running, then it runs
+each at 50% physical power --- i.e., actually in parallel.
+
+On real hardware, we can run only a single task at once, so we have to
+introduce the concept of "virtual runtime." The virtual runtime of a task
+specifies when its next timeslice would start execution on the ideal
+multi-tasking CPU described above. In practice, the virtual runtime of a task
+is its actual runtime normalized to the total number of running tasks.
+
+
+
+2. FEW IMPLEMENTATION DETAILS
+==============================
+
+In CFS the virtual runtime is expressed and tracked via the per-task
+p->se.vruntime (nanosec-unit) value. This way, it's possible to accurately
+timestamp and measure the "expected CPU time" a task should have gotten.
+
+[ small detail: on "ideal" hardware, at any time all tasks would have the same
+ p->se.vruntime value --- i.e., tasks would execute simultaneously and no task
+ would ever get "out of balance" from the "ideal" share of CPU time. ]
+
+CFS's task picking logic is based on this p->se.vruntime value and it is thus
+very simple: it always tries to run the task with the smallest p->se.vruntime
+value (i.e., the task which executed least so far). CFS always tries to split
+up CPU time between runnable tasks as close to "ideal multitasking hardware" as
+possible.
+
+Most of the rest of CFS's design just falls out of this really simple concept,
+with a few add-on embellishments like nice levels, multiprocessing and various
+algorithm variants to recognize sleepers.
+
+
+
+3. THE RBTREE
+==============
+
+CFS's design is quite radical: it does not use the old data structures for the
+runqueues, but it uses a time-ordered rbtree to build a "timeline" of future
+task execution, and thus has no "array switch" artifacts (by which both the
+previous vanilla scheduler and RSDL/SD are affected).
+
+CFS also maintains the rq->cfs.min_vruntime value, which is a monotonic
+increasing value tracking the smallest vruntime among all tasks in the
+runqueue. The total amount of work done by the system is tracked using
+min_vruntime; that value is used to place newly activated entities on the left
+side of the tree as much as possible.
+
+The total number of running tasks in the runqueue is accounted through the
+rq->cfs.load value, which is the sum of the weights of the tasks queued on the
+runqueue.
+
+CFS maintains a time-ordered rbtree, where all runnable tasks are sorted by the
+p->se.vruntime key. CFS picks the "leftmost" task from this tree and sticks to it.
+As the system progresses forwards, the executed tasks are put into the tree
+more and more to the right --- slowly but surely giving a chance for every task
+to become the "leftmost task" and thus get on the CPU within a deterministic
+amount of time.
+
+Summing up, CFS works like this: it runs a task a bit, and when the task
+schedules (or a scheduler tick happens) the task's CPU usage is "accounted
+for": the (small) time it just spent using the physical CPU is added to
+p->se.vruntime. Once p->se.vruntime gets high enough so that another task
+becomes the "leftmost task" of the time-ordered rbtree it maintains (plus a
+small amount of "granularity" distance relative to the leftmost task so that we
+do not over-schedule tasks and trash the cache), then the new leftmost task is
+picked and the current task is preempted.
+
+
+
+4. SOME FEATURES OF CFS
+========================
+
+CFS uses nanosecond granularity accounting and does not rely on any jiffies or
+other HZ detail. Thus the CFS scheduler has no notion of "timeslices" in the
+way the previous scheduler had, and has no heuristics whatsoever. There is
+only one central tunable (you have to switch on CONFIG_SCHED_DEBUG):
+
+ /proc/sys/kernel/sched_min_granularity_ns
+
+which can be used to tune the scheduler from "desktop" (i.e., low latencies) to
+"server" (i.e., good batching) workloads. It defaults to a setting suitable
+for desktop workloads. SCHED_BATCH is handled by the CFS scheduler module too.
+
+Due to its design, the CFS scheduler is not prone to any of the "attacks" that
+exist today against the heuristics of the stock scheduler: fiftyp.c, thud.c,
+chew.c, ring-test.c, massive_intr.c all work fine and do not impact
+interactivity and produce the expected behavior.
+
+The CFS scheduler has a much stronger handling of nice levels and SCHED_BATCH
+than the previous vanilla scheduler: both types of workloads are isolated much
+more aggressively.
+
+SMP load-balancing has been reworked/sanitized: the runqueue-walking
+assumptions are gone from the load-balancing code now, and iterators of the
+scheduling modules are used. The balancing code got quite a bit simpler as a
+result.
+
+
+
+5. Scheduling policies
+======================
+
+CFS implements three scheduling policies:
+
+ - SCHED_NORMAL (traditionally called SCHED_OTHER): The scheduling
+ policy that is used for regular tasks.
+
+ - SCHED_BATCH: Does not preempt nearly as often as regular tasks
+ would, thereby allowing tasks to run longer and make better use of
+ caches but at the cost of interactivity. This is well suited for
+ batch jobs.
+
+ - SCHED_IDLE: This is even weaker than nice 19, but its not a true
+ idle timer scheduler in order to avoid to get into priority
+ inversion problems which would deadlock the machine.
+
+SCHED_FIFO/_RR are implemented in sched/rt.c and are as specified by
+POSIX.
+
+The command chrt from util-linux-ng 2.13.1.1 can set all of these except
+SCHED_IDLE.
+
+
+
+6. SCHEDULING CLASSES
+======================
+
+The new CFS scheduler has been designed in such a way to introduce "Scheduling
+Classes," an extensible hierarchy of scheduler modules. These modules
+encapsulate scheduling policy details and are handled by the scheduler core
+without the core code assuming too much about them.
+
+sched/fair.c implements the CFS scheduler described above.
+
+sched/rt.c implements SCHED_FIFO and SCHED_RR semantics, in a simpler way than
+the previous vanilla scheduler did. It uses 100 runqueues (for all 100 RT
+priority levels, instead of 140 in the previous scheduler) and it needs no
+expired array.
+
+Scheduling classes are implemented through the sched_class structure, which
+contains hooks to functions that must be called whenever an interesting event
+occurs.
+
+This is the (partial) list of the hooks:
+
+ - enqueue_task(...)
+
+ Called when a task enters a runnable state.
+ It puts the scheduling entity (task) into the red-black tree and
+ increments the nr_running variable.
+
+ - dequeue_task(...)
+
+ When a task is no longer runnable, this function is called to keep the
+ corresponding scheduling entity out of the red-black tree. It decrements
+ the nr_running variable.
+
+ - yield_task(...)
+
+ This function is basically just a dequeue followed by an enqueue, unless the
+ compat_yield sysctl is turned on; in that case, it places the scheduling
+ entity at the right-most end of the red-black tree.
+
+ - check_preempt_curr(...)
+
+ This function checks if a task that entered the runnable state should
+ preempt the currently running task.
+
+ - pick_next_task(...)
+
+ This function chooses the most appropriate task eligible to run next.
+
+ - set_curr_task(...)
+
+ This function is called when a task changes its scheduling class or changes
+ its task group.
+
+ - task_tick(...)
+
+ This function is mostly called from time tick functions; it might lead to
+ process switch. This drives the running preemption.
+
+
+
+
+7. GROUP SCHEDULER EXTENSIONS TO CFS
+=====================================
+
+Normally, the scheduler operates on individual tasks and strives to provide
+fair CPU time to each task. Sometimes, it may be desirable to group tasks and
+provide fair CPU time to each such task group. For example, it may be
+desirable to first provide fair CPU time to each user on the system and then to
+each task belonging to a user.
+
+CONFIG_CGROUP_SCHED strives to achieve exactly that. It lets tasks to be
+grouped and divides CPU time fairly among such groups.
+
+CONFIG_RT_GROUP_SCHED permits to group real-time (i.e., SCHED_FIFO and
+SCHED_RR) tasks.
+
+CONFIG_FAIR_GROUP_SCHED permits to group CFS (i.e., SCHED_NORMAL and
+SCHED_BATCH) tasks.
+
+ These options need CONFIG_CGROUPS to be defined, and let the administrator
+ create arbitrary groups of tasks, using the "cgroup" pseudo filesystem. See
+ Documentation/cgroup-v1/cgroups.txt for more information about this filesystem.
+
+When CONFIG_FAIR_GROUP_SCHED is defined, a "cpu.shares" file is created for each
+group created using the pseudo filesystem. See example steps below to create
+task groups and modify their CPU share using the "cgroups" pseudo filesystem::
+
+ # mount -t tmpfs cgroup_root /sys/fs/cgroup
+ # mkdir /sys/fs/cgroup/cpu
+ # mount -t cgroup -ocpu none /sys/fs/cgroup/cpu
+ # cd /sys/fs/cgroup/cpu
+
+ # mkdir multimedia # create "multimedia" group of tasks
+ # mkdir browser # create "browser" group of tasks
+
+ # #Configure the multimedia group to receive twice the CPU bandwidth
+ # #that of browser group
+
+ # echo 2048 > multimedia/cpu.shares
+ # echo 1024 > browser/cpu.shares
+
+ # firefox & # Launch firefox and move it to "browser" group
+ # echo <firefox_pid> > browser/tasks
+
+ # #Launch gmplayer (or your favourite movie player)
+ # echo <movie_player_pid> > multimedia/tasks
+++ /dev/null
- =============
- CFS Scheduler
- =============
-
-
-1. OVERVIEW
-
-CFS stands for "Completely Fair Scheduler," and is the new "desktop" process
-scheduler implemented by Ingo Molnar and merged in Linux 2.6.23. It is the
-replacement for the previous vanilla scheduler's SCHED_OTHER interactivity
-code.
-
-80% of CFS's design can be summed up in a single sentence: CFS basically models
-an "ideal, precise multi-tasking CPU" on real hardware.
-
-"Ideal multi-tasking CPU" is a (non-existent :-)) CPU that has 100% physical
-power and which can run each task at precise equal speed, in parallel, each at
-1/nr_running speed. For example: if there are 2 tasks running, then it runs
-each at 50% physical power --- i.e., actually in parallel.
-
-On real hardware, we can run only a single task at once, so we have to
-introduce the concept of "virtual runtime." The virtual runtime of a task
-specifies when its next timeslice would start execution on the ideal
-multi-tasking CPU described above. In practice, the virtual runtime of a task
-is its actual runtime normalized to the total number of running tasks.
-
-
-
-2. FEW IMPLEMENTATION DETAILS
-
-In CFS the virtual runtime is expressed and tracked via the per-task
-p->se.vruntime (nanosec-unit) value. This way, it's possible to accurately
-timestamp and measure the "expected CPU time" a task should have gotten.
-
-[ small detail: on "ideal" hardware, at any time all tasks would have the same
- p->se.vruntime value --- i.e., tasks would execute simultaneously and no task
- would ever get "out of balance" from the "ideal" share of CPU time. ]
-
-CFS's task picking logic is based on this p->se.vruntime value and it is thus
-very simple: it always tries to run the task with the smallest p->se.vruntime
-value (i.e., the task which executed least so far). CFS always tries to split
-up CPU time between runnable tasks as close to "ideal multitasking hardware" as
-possible.
-
-Most of the rest of CFS's design just falls out of this really simple concept,
-with a few add-on embellishments like nice levels, multiprocessing and various
-algorithm variants to recognize sleepers.
-
-
-
-3. THE RBTREE
-
-CFS's design is quite radical: it does not use the old data structures for the
-runqueues, but it uses a time-ordered rbtree to build a "timeline" of future
-task execution, and thus has no "array switch" artifacts (by which both the
-previous vanilla scheduler and RSDL/SD are affected).
-
-CFS also maintains the rq->cfs.min_vruntime value, which is a monotonic
-increasing value tracking the smallest vruntime among all tasks in the
-runqueue. The total amount of work done by the system is tracked using
-min_vruntime; that value is used to place newly activated entities on the left
-side of the tree as much as possible.
-
-The total number of running tasks in the runqueue is accounted through the
-rq->cfs.load value, which is the sum of the weights of the tasks queued on the
-runqueue.
-
-CFS maintains a time-ordered rbtree, where all runnable tasks are sorted by the
-p->se.vruntime key. CFS picks the "leftmost" task from this tree and sticks to it.
-As the system progresses forwards, the executed tasks are put into the tree
-more and more to the right --- slowly but surely giving a chance for every task
-to become the "leftmost task" and thus get on the CPU within a deterministic
-amount of time.
-
-Summing up, CFS works like this: it runs a task a bit, and when the task
-schedules (or a scheduler tick happens) the task's CPU usage is "accounted
-for": the (small) time it just spent using the physical CPU is added to
-p->se.vruntime. Once p->se.vruntime gets high enough so that another task
-becomes the "leftmost task" of the time-ordered rbtree it maintains (plus a
-small amount of "granularity" distance relative to the leftmost task so that we
-do not over-schedule tasks and trash the cache), then the new leftmost task is
-picked and the current task is preempted.
-
-
-
-4. SOME FEATURES OF CFS
-
-CFS uses nanosecond granularity accounting and does not rely on any jiffies or
-other HZ detail. Thus the CFS scheduler has no notion of "timeslices" in the
-way the previous scheduler had, and has no heuristics whatsoever. There is
-only one central tunable (you have to switch on CONFIG_SCHED_DEBUG):
-
- /proc/sys/kernel/sched_min_granularity_ns
-
-which can be used to tune the scheduler from "desktop" (i.e., low latencies) to
-"server" (i.e., good batching) workloads. It defaults to a setting suitable
-for desktop workloads. SCHED_BATCH is handled by the CFS scheduler module too.
-
-Due to its design, the CFS scheduler is not prone to any of the "attacks" that
-exist today against the heuristics of the stock scheduler: fiftyp.c, thud.c,
-chew.c, ring-test.c, massive_intr.c all work fine and do not impact
-interactivity and produce the expected behavior.
-
-The CFS scheduler has a much stronger handling of nice levels and SCHED_BATCH
-than the previous vanilla scheduler: both types of workloads are isolated much
-more aggressively.
-
-SMP load-balancing has been reworked/sanitized: the runqueue-walking
-assumptions are gone from the load-balancing code now, and iterators of the
-scheduling modules are used. The balancing code got quite a bit simpler as a
-result.
-
-
-
-5. Scheduling policies
-
-CFS implements three scheduling policies:
-
- - SCHED_NORMAL (traditionally called SCHED_OTHER): The scheduling
- policy that is used for regular tasks.
-
- - SCHED_BATCH: Does not preempt nearly as often as regular tasks
- would, thereby allowing tasks to run longer and make better use of
- caches but at the cost of interactivity. This is well suited for
- batch jobs.
-
- - SCHED_IDLE: This is even weaker than nice 19, but its not a true
- idle timer scheduler in order to avoid to get into priority
- inversion problems which would deadlock the machine.
-
-SCHED_FIFO/_RR are implemented in sched/rt.c and are as specified by
-POSIX.
-
-The command chrt from util-linux-ng 2.13.1.1 can set all of these except
-SCHED_IDLE.
-
-
-
-6. SCHEDULING CLASSES
-
-The new CFS scheduler has been designed in such a way to introduce "Scheduling
-Classes," an extensible hierarchy of scheduler modules. These modules
-encapsulate scheduling policy details and are handled by the scheduler core
-without the core code assuming too much about them.
-
-sched/fair.c implements the CFS scheduler described above.
-
-sched/rt.c implements SCHED_FIFO and SCHED_RR semantics, in a simpler way than
-the previous vanilla scheduler did. It uses 100 runqueues (for all 100 RT
-priority levels, instead of 140 in the previous scheduler) and it needs no
-expired array.
-
-Scheduling classes are implemented through the sched_class structure, which
-contains hooks to functions that must be called whenever an interesting event
-occurs.
-
-This is the (partial) list of the hooks:
-
- - enqueue_task(...)
-
- Called when a task enters a runnable state.
- It puts the scheduling entity (task) into the red-black tree and
- increments the nr_running variable.
-
- - dequeue_task(...)
-
- When a task is no longer runnable, this function is called to keep the
- corresponding scheduling entity out of the red-black tree. It decrements
- the nr_running variable.
-
- - yield_task(...)
-
- This function is basically just a dequeue followed by an enqueue, unless the
- compat_yield sysctl is turned on; in that case, it places the scheduling
- entity at the right-most end of the red-black tree.
-
- - check_preempt_curr(...)
-
- This function checks if a task that entered the runnable state should
- preempt the currently running task.
-
- - pick_next_task(...)
-
- This function chooses the most appropriate task eligible to run next.
-
- - set_curr_task(...)
-
- This function is called when a task changes its scheduling class or changes
- its task group.
-
- - task_tick(...)
-
- This function is mostly called from time tick functions; it might lead to
- process switch. This drives the running preemption.
-
-
-
-
-7. GROUP SCHEDULER EXTENSIONS TO CFS
-
-Normally, the scheduler operates on individual tasks and strives to provide
-fair CPU time to each task. Sometimes, it may be desirable to group tasks and
-provide fair CPU time to each such task group. For example, it may be
-desirable to first provide fair CPU time to each user on the system and then to
-each task belonging to a user.
-
-CONFIG_CGROUP_SCHED strives to achieve exactly that. It lets tasks to be
-grouped and divides CPU time fairly among such groups.
-
-CONFIG_RT_GROUP_SCHED permits to group real-time (i.e., SCHED_FIFO and
-SCHED_RR) tasks.
-
-CONFIG_FAIR_GROUP_SCHED permits to group CFS (i.e., SCHED_NORMAL and
-SCHED_BATCH) tasks.
-
- These options need CONFIG_CGROUPS to be defined, and let the administrator
- create arbitrary groups of tasks, using the "cgroup" pseudo filesystem. See
- Documentation/cgroup-v1/cgroups.txt for more information about this filesystem.
-
-When CONFIG_FAIR_GROUP_SCHED is defined, a "cpu.shares" file is created for each
-group created using the pseudo filesystem. See example steps below to create
-task groups and modify their CPU share using the "cgroups" pseudo filesystem.
-
- # mount -t tmpfs cgroup_root /sys/fs/cgroup
- # mkdir /sys/fs/cgroup/cpu
- # mount -t cgroup -ocpu none /sys/fs/cgroup/cpu
- # cd /sys/fs/cgroup/cpu
-
- # mkdir multimedia # create "multimedia" group of tasks
- # mkdir browser # create "browser" group of tasks
-
- # #Configure the multimedia group to receive twice the CPU bandwidth
- # #that of browser group
-
- # echo 2048 > multimedia/cpu.shares
- # echo 1024 > browser/cpu.shares
-
- # firefox & # Launch firefox and move it to "browser" group
- # echo <firefox_pid> > browser/tasks
-
- # #Launch gmplayer (or your favourite movie player)
- # echo <movie_player_pid> > multimedia/tasks
--- /dev/null
+=================
+Scheduler Domains
+=================
+
+Each CPU has a "base" scheduling domain (struct sched_domain). The domain
+hierarchy is built from these base domains via the ->parent pointer. ->parent
+MUST be NULL terminated, and domain structures should be per-CPU as they are
+locklessly updated.
+
+Each scheduling domain spans a number of CPUs (stored in the ->span field).
+A domain's span MUST be a superset of it child's span (this restriction could
+be relaxed if the need arises), and a base domain for CPU i MUST span at least
+i. The top domain for each CPU will generally span all CPUs in the system
+although strictly it doesn't have to, but this could lead to a case where some
+CPUs will never be given tasks to run unless the CPUs allowed mask is
+explicitly set. A sched domain's span means "balance process load among these
+CPUs".
+
+Each scheduling domain must have one or more CPU groups (struct sched_group)
+which are organised as a circular one way linked list from the ->groups
+pointer. The union of cpumasks of these groups MUST be the same as the
+domain's span. The intersection of cpumasks from any two of these groups
+MUST be the empty set. The group pointed to by the ->groups pointer MUST
+contain the CPU to which the domain belongs. Groups may be shared among
+CPUs as they contain read only data after they have been set up.
+
+Balancing within a sched domain occurs between groups. That is, each group
+is treated as one entity. The load of a group is defined as the sum of the
+load of each of its member CPUs, and only when the load of a group becomes
+out of balance are tasks moved between groups.
+
+In kernel/sched/core.c, trigger_load_balance() is run periodically on each CPU
+through scheduler_tick(). It raises a softirq after the next regularly scheduled
+rebalancing event for the current runqueue has arrived. The actual load
+balancing workhorse, run_rebalance_domains()->rebalance_domains(), is then run
+in softirq context (SCHED_SOFTIRQ).
+
+The latter function takes two arguments: the current CPU and whether it was idle
+at the time the scheduler_tick() happened and iterates over all sched domains
+our CPU is on, starting from its base domain and going up the ->parent chain.
+While doing that, it checks to see if the current domain has exhausted its
+rebalance interval. If so, it runs load_balance() on that domain. It then checks
+the parent sched_domain (if it exists), and the parent of the parent and so
+forth.
+
+Initially, load_balance() finds the busiest group in the current sched domain.
+If it succeeds, it looks for the busiest runqueue of all the CPUs' runqueues in
+that group. If it manages to find such a runqueue, it locks both our initial
+CPU's runqueue and the newly found busiest one and starts moving tasks from it
+to our runqueue. The exact number of tasks amounts to an imbalance previously
+computed while iterating over this sched domain's groups.
+
+Implementing sched domains
+==========================
+
+The "base" domain will "span" the first level of the hierarchy. In the case
+of SMT, you'll span all siblings of the physical CPU, with each group being
+a single virtual CPU.
+
+In SMP, the parent of the base domain will span all physical CPUs in the
+node. Each group being a single physical CPU. Then with NUMA, the parent
+of the SMP domain will span the entire machine, with each group having the
+cpumask of a node. Or, you could do multi-level NUMA or Opteron, for example,
+might have just one domain covering its one NUMA level.
+
+The implementor should read comments in include/linux/sched.h:
+struct sched_domain fields, SD_FLAG_*, SD_*_INIT to get an idea of
+the specifics and what to tune.
+
+Architectures may retain the regular override the default SD_*_INIT flags
+while using the generic domain builder in kernel/sched/core.c if they wish to
+retain the traditional SMT->SMP->NUMA topology (or some subset of that). This
+can be done by #define'ing ARCH_HASH_SCHED_TUNE.
+
+Alternatively, the architecture may completely override the generic domain
+builder by #define'ing ARCH_HASH_SCHED_DOMAIN, and exporting your
+arch_init_sched_domains function. This function will attach domains to all
+CPUs using cpu_attach_domain.
+
+The sched-domains debugging infrastructure can be enabled by enabling
+CONFIG_SCHED_DEBUG. This enables an error checking parse of the sched domains
+which should catch most possible errors (described above). It also prints out
+the domain structure in a visual format.
+++ /dev/null
-Each CPU has a "base" scheduling domain (struct sched_domain). The domain
-hierarchy is built from these base domains via the ->parent pointer. ->parent
-MUST be NULL terminated, and domain structures should be per-CPU as they are
-locklessly updated.
-
-Each scheduling domain spans a number of CPUs (stored in the ->span field).
-A domain's span MUST be a superset of it child's span (this restriction could
-be relaxed if the need arises), and a base domain for CPU i MUST span at least
-i. The top domain for each CPU will generally span all CPUs in the system
-although strictly it doesn't have to, but this could lead to a case where some
-CPUs will never be given tasks to run unless the CPUs allowed mask is
-explicitly set. A sched domain's span means "balance process load among these
-CPUs".
-
-Each scheduling domain must have one or more CPU groups (struct sched_group)
-which are organised as a circular one way linked list from the ->groups
-pointer. The union of cpumasks of these groups MUST be the same as the
-domain's span. The intersection of cpumasks from any two of these groups
-MUST be the empty set. The group pointed to by the ->groups pointer MUST
-contain the CPU to which the domain belongs. Groups may be shared among
-CPUs as they contain read only data after they have been set up.
-
-Balancing within a sched domain occurs between groups. That is, each group
-is treated as one entity. The load of a group is defined as the sum of the
-load of each of its member CPUs, and only when the load of a group becomes
-out of balance are tasks moved between groups.
-
-In kernel/sched/core.c, trigger_load_balance() is run periodically on each CPU
-through scheduler_tick(). It raises a softirq after the next regularly scheduled
-rebalancing event for the current runqueue has arrived. The actual load
-balancing workhorse, run_rebalance_domains()->rebalance_domains(), is then run
-in softirq context (SCHED_SOFTIRQ).
-
-The latter function takes two arguments: the current CPU and whether it was idle
-at the time the scheduler_tick() happened and iterates over all sched domains
-our CPU is on, starting from its base domain and going up the ->parent chain.
-While doing that, it checks to see if the current domain has exhausted its
-rebalance interval. If so, it runs load_balance() on that domain. It then checks
-the parent sched_domain (if it exists), and the parent of the parent and so
-forth.
-
-Initially, load_balance() finds the busiest group in the current sched domain.
-If it succeeds, it looks for the busiest runqueue of all the CPUs' runqueues in
-that group. If it manages to find such a runqueue, it locks both our initial
-CPU's runqueue and the newly found busiest one and starts moving tasks from it
-to our runqueue. The exact number of tasks amounts to an imbalance previously
-computed while iterating over this sched domain's groups.
-
-*** Implementing sched domains ***
-The "base" domain will "span" the first level of the hierarchy. In the case
-of SMT, you'll span all siblings of the physical CPU, with each group being
-a single virtual CPU.
-
-In SMP, the parent of the base domain will span all physical CPUs in the
-node. Each group being a single physical CPU. Then with NUMA, the parent
-of the SMP domain will span the entire machine, with each group having the
-cpumask of a node. Or, you could do multi-level NUMA or Opteron, for example,
-might have just one domain covering its one NUMA level.
-
-The implementor should read comments in include/linux/sched.h:
-struct sched_domain fields, SD_FLAG_*, SD_*_INIT to get an idea of
-the specifics and what to tune.
-
-Architectures may retain the regular override the default SD_*_INIT flags
-while using the generic domain builder in kernel/sched/core.c if they wish to
-retain the traditional SMT->SMP->NUMA topology (or some subset of that). This
-can be done by #define'ing ARCH_HASH_SCHED_TUNE.
-
-Alternatively, the architecture may completely override the generic domain
-builder by #define'ing ARCH_HASH_SCHED_DOMAIN, and exporting your
-arch_init_sched_domains function. This function will attach domains to all
-CPUs using cpu_attach_domain.
-
-The sched-domains debugging infrastructure can be enabled by enabling
-CONFIG_SCHED_DEBUG. This enables an error checking parse of the sched domains
-which should catch most possible errors (described above). It also prints out
-the domain structure in a visual format.
--- /dev/null
+=======================
+Energy Aware Scheduling
+=======================
+
+1. Introduction
+---------------
+
+Energy Aware Scheduling (or EAS) gives the scheduler the ability to predict
+the impact of its decisions on the energy consumed by CPUs. EAS relies on an
+Energy Model (EM) of the CPUs to select an energy efficient CPU for each task,
+with a minimal impact on throughput. This document aims at providing an
+introduction on how EAS works, what are the main design decisions behind it, and
+details what is needed to get it to run.
+
+Before going any further, please note that at the time of writing::
+
+ /!\ EAS does not support platforms with symmetric CPU topologies /!\
+
+EAS operates only on heterogeneous CPU topologies (such as Arm big.LITTLE)
+because this is where the potential for saving energy through scheduling is
+the highest.
+
+The actual EM used by EAS is _not_ maintained by the scheduler, but by a
+dedicated framework. For details about this framework and what it provides,
+please refer to its documentation (see Documentation/power/energy-model.txt).
+
+
+2. Background and Terminology
+-----------------------------
+
+To make it clear from the start:
+ - energy = [joule] (resource like a battery on powered devices)
+ - power = energy/time = [joule/second] = [watt]
+
+The goal of EAS is to minimize energy, while still getting the job done. That
+is, we want to maximize::
+
+ performance [inst/s]
+ --------------------
+ power [W]
+
+which is equivalent to minimizing::
+
+ energy [J]
+ -----------
+ instruction
+
+while still getting 'good' performance. It is essentially an alternative
+optimization objective to the current performance-only objective for the
+scheduler. This alternative considers two objectives: energy-efficiency and
+performance.
+
+The idea behind introducing an EM is to allow the scheduler to evaluate the
+implications of its decisions rather than blindly applying energy-saving
+techniques that may have positive effects only on some platforms. At the same
+time, the EM must be as simple as possible to minimize the scheduler latency
+impact.
+
+In short, EAS changes the way CFS tasks are assigned to CPUs. When it is time
+for the scheduler to decide where a task should run (during wake-up), the EM
+is used to break the tie between several good CPU candidates and pick the one
+that is predicted to yield the best energy consumption without harming the
+system's throughput. The predictions made by EAS rely on specific elements of
+knowledge about the platform's topology, which include the 'capacity' of CPUs,
+and their respective energy costs.
+
+
+3. Topology information
+-----------------------
+
+EAS (as well as the rest of the scheduler) uses the notion of 'capacity' to
+differentiate CPUs with different computing throughput. The 'capacity' of a CPU
+represents the amount of work it can absorb when running at its highest
+frequency compared to the most capable CPU of the system. Capacity values are
+normalized in a 1024 range, and are comparable with the utilization signals of
+tasks and CPUs computed by the Per-Entity Load Tracking (PELT) mechanism. Thanks
+to capacity and utilization values, EAS is able to estimate how big/busy a
+task/CPU is, and to take this into consideration when evaluating performance vs
+energy trade-offs. The capacity of CPUs is provided via arch-specific code
+through the arch_scale_cpu_capacity() callback.
+
+The rest of platform knowledge used by EAS is directly read from the Energy
+Model (EM) framework. The EM of a platform is composed of a power cost table
+per 'performance domain' in the system (see Documentation/power/energy-model.txt
+for futher details about performance domains).
+
+The scheduler manages references to the EM objects in the topology code when the
+scheduling domains are built, or re-built. For each root domain (rd), the
+scheduler maintains a singly linked list of all performance domains intersecting
+the current rd->span. Each node in the list contains a pointer to a struct
+em_perf_domain as provided by the EM framework.
+
+The lists are attached to the root domains in order to cope with exclusive
+cpuset configurations. Since the boundaries of exclusive cpusets do not
+necessarily match those of performance domains, the lists of different root
+domains can contain duplicate elements.
+
+Example 1.
+ Let us consider a platform with 12 CPUs, split in 3 performance domains
+ (pd0, pd4 and pd8), organized as follows::
+
+ CPUs: 0 1 2 3 4 5 6 7 8 9 10 11
+ PDs: |--pd0--|--pd4--|---pd8---|
+ RDs: |----rd1----|-----rd2-----|
+
+ Now, consider that userspace decided to split the system with two
+ exclusive cpusets, hence creating two independent root domains, each
+ containing 6 CPUs. The two root domains are denoted rd1 and rd2 in the
+ above figure. Since pd4 intersects with both rd1 and rd2, it will be
+ present in the linked list '->pd' attached to each of them:
+
+ * rd1->pd: pd0 -> pd4
+ * rd2->pd: pd4 -> pd8
+
+ Please note that the scheduler will create two duplicate list nodes for
+ pd4 (one for each list). However, both just hold a pointer to the same
+ shared data structure of the EM framework.
+
+Since the access to these lists can happen concurrently with hotplug and other
+things, they are protected by RCU, like the rest of topology structures
+manipulated by the scheduler.
+
+EAS also maintains a static key (sched_energy_present) which is enabled when at
+least one root domain meets all conditions for EAS to start. Those conditions
+are summarized in Section 6.
+
+
+4. Energy-Aware task placement
+------------------------------
+
+EAS overrides the CFS task wake-up balancing code. It uses the EM of the
+platform and the PELT signals to choose an energy-efficient target CPU during
+wake-up balance. When EAS is enabled, select_task_rq_fair() calls
+find_energy_efficient_cpu() to do the placement decision. This function looks
+for the CPU with the highest spare capacity (CPU capacity - CPU utilization) in
+each performance domain since it is the one which will allow us to keep the
+frequency the lowest. Then, the function checks if placing the task there could
+save energy compared to leaving it on prev_cpu, i.e. the CPU where the task ran
+in its previous activation.
+
+find_energy_efficient_cpu() uses compute_energy() to estimate what will be the
+energy consumed by the system if the waking task was migrated. compute_energy()
+looks at the current utilization landscape of the CPUs and adjusts it to
+'simulate' the task migration. The EM framework provides the em_pd_energy() API
+which computes the expected energy consumption of each performance domain for
+the given utilization landscape.
+
+An example of energy-optimized task placement decision is detailed below.
+
+Example 2.
+ Let us consider a (fake) platform with 2 independent performance domains
+ composed of two CPUs each. CPU0 and CPU1 are little CPUs; CPU2 and CPU3
+ are big.
+
+ The scheduler must decide where to place a task P whose util_avg = 200
+ and prev_cpu = 0.
+
+ The current utilization landscape of the CPUs is depicted on the graph
+ below. CPUs 0-3 have a util_avg of 400, 100, 600 and 500 respectively
+ Each performance domain has three Operating Performance Points (OPPs).
+ The CPU capacity and power cost associated with each OPP is listed in
+ the Energy Model table. The util_avg of P is shown on the figures
+ below as 'PP'::
+
+ CPU util.
+ 1024 - - - - - - - Energy Model
+ +-----------+-------------+
+ | Little | Big |
+ 768 ============= +-----+-----+------+------+
+ | Cap | Pwr | Cap | Pwr |
+ +-----+-----+------+------+
+ 512 =========== - ##- - - - - | 170 | 50 | 512 | 400 |
+ ## ## | 341 | 150 | 768 | 800 |
+ 341 -PP - - - - ## ## | 512 | 300 | 1024 | 1700 |
+ PP ## ## +-----+-----+------+------+
+ 170 -## - - - - ## ##
+ ## ## ## ##
+ ------------ -------------
+ CPU0 CPU1 CPU2 CPU3
+
+ Current OPP: ===== Other OPP: - - - util_avg (100 each): ##
+
+
+ find_energy_efficient_cpu() will first look for the CPUs with the
+ maximum spare capacity in the two performance domains. In this example,
+ CPU1 and CPU3. Then it will estimate the energy of the system if P was
+ placed on either of them, and check if that would save some energy
+ compared to leaving P on CPU0. EAS assumes that OPPs follow utilization
+ (which is coherent with the behaviour of the schedutil CPUFreq
+ governor, see Section 6. for more details on this topic).
+
+ **Case 1. P is migrated to CPU1**::
+
+ 1024 - - - - - - -
+
+ Energy calculation:
+ 768 ============= * CPU0: 200 / 341 * 150 = 88
+ * CPU1: 300 / 341 * 150 = 131
+ * CPU2: 600 / 768 * 800 = 625
+ 512 - - - - - - - ##- - - - - * CPU3: 500 / 768 * 800 = 520
+ ## ## => total_energy = 1364
+ 341 =========== ## ##
+ PP ## ##
+ 170 -## - - PP- ## ##
+ ## ## ## ##
+ ------------ -------------
+ CPU0 CPU1 CPU2 CPU3
+
+
+ **Case 2. P is migrated to CPU3**::
+
+ 1024 - - - - - - -
+
+ Energy calculation:
+ 768 ============= * CPU0: 200 / 341 * 150 = 88
+ * CPU1: 100 / 341 * 150 = 43
+ PP * CPU2: 600 / 768 * 800 = 625
+ 512 - - - - - - - ##- - -PP - * CPU3: 700 / 768 * 800 = 729
+ ## ## => total_energy = 1485
+ 341 =========== ## ##
+ ## ##
+ 170 -## - - - - ## ##
+ ## ## ## ##
+ ------------ -------------
+ CPU0 CPU1 CPU2 CPU3
+
+
+ **Case 3. P stays on prev_cpu / CPU 0**::
+
+ 1024 - - - - - - -
+
+ Energy calculation:
+ 768 ============= * CPU0: 400 / 512 * 300 = 234
+ * CPU1: 100 / 512 * 300 = 58
+ * CPU2: 600 / 768 * 800 = 625
+ 512 =========== - ##- - - - - * CPU3: 500 / 768 * 800 = 520
+ ## ## => total_energy = 1437
+ 341 -PP - - - - ## ##
+ PP ## ##
+ 170 -## - - - - ## ##
+ ## ## ## ##
+ ------------ -------------
+ CPU0 CPU1 CPU2 CPU3
+
+
+ From these calculations, the Case 1 has the lowest total energy. So CPU 1
+ is be the best candidate from an energy-efficiency standpoint.
+
+Big CPUs are generally more power hungry than the little ones and are thus used
+mainly when a task doesn't fit the littles. However, little CPUs aren't always
+necessarily more energy-efficient than big CPUs. For some systems, the high OPPs
+of the little CPUs can be less energy-efficient than the lowest OPPs of the
+bigs, for example. So, if the little CPUs happen to have enough utilization at
+a specific point in time, a small task waking up at that moment could be better
+of executing on the big side in order to save energy, even though it would fit
+on the little side.
+
+And even in the case where all OPPs of the big CPUs are less energy-efficient
+than those of the little, using the big CPUs for a small task might still, under
+specific conditions, save energy. Indeed, placing a task on a little CPU can
+result in raising the OPP of the entire performance domain, and that will
+increase the cost of the tasks already running there. If the waking task is
+placed on a big CPU, its own execution cost might be higher than if it was
+running on a little, but it won't impact the other tasks of the little CPUs
+which will keep running at a lower OPP. So, when considering the total energy
+consumed by CPUs, the extra cost of running that one task on a big core can be
+smaller than the cost of raising the OPP on the little CPUs for all the other
+tasks.
+
+The examples above would be nearly impossible to get right in a generic way, and
+for all platforms, without knowing the cost of running at different OPPs on all
+CPUs of the system. Thanks to its EM-based design, EAS should cope with them
+correctly without too many troubles. However, in order to ensure a minimal
+impact on throughput for high-utilization scenarios, EAS also implements another
+mechanism called 'over-utilization'.
+
+
+5. Over-utilization
+-------------------
+
+From a general standpoint, the use-cases where EAS can help the most are those
+involving a light/medium CPU utilization. Whenever long CPU-bound tasks are
+being run, they will require all of the available CPU capacity, and there isn't
+much that can be done by the scheduler to save energy without severly harming
+throughput. In order to avoid hurting performance with EAS, CPUs are flagged as
+'over-utilized' as soon as they are used at more than 80% of their compute
+capacity. As long as no CPUs are over-utilized in a root domain, load balancing
+is disabled and EAS overridess the wake-up balancing code. EAS is likely to load
+the most energy efficient CPUs of the system more than the others if that can be
+done without harming throughput. So, the load-balancer is disabled to prevent
+it from breaking the energy-efficient task placement found by EAS. It is safe to
+do so when the system isn't overutilized since being below the 80% tipping point
+implies that:
+
+ a. there is some idle time on all CPUs, so the utilization signals used by
+ EAS are likely to accurately represent the 'size' of the various tasks
+ in the system;
+ b. all tasks should already be provided with enough CPU capacity,
+ regardless of their nice values;
+ c. since there is spare capacity all tasks must be blocking/sleeping
+ regularly and balancing at wake-up is sufficient.
+
+As soon as one CPU goes above the 80% tipping point, at least one of the three
+assumptions above becomes incorrect. In this scenario, the 'overutilized' flag
+is raised for the entire root domain, EAS is disabled, and the load-balancer is
+re-enabled. By doing so, the scheduler falls back onto load-based algorithms for
+wake-up and load balance under CPU-bound conditions. This provides a better
+respect of the nice values of tasks.
+
+Since the notion of overutilization largely relies on detecting whether or not
+there is some idle time in the system, the CPU capacity 'stolen' by higher
+(than CFS) scheduling classes (as well as IRQ) must be taken into account. As
+such, the detection of overutilization accounts for the capacity used not only
+by CFS tasks, but also by the other scheduling classes and IRQ.
+
+
+6. Dependencies and requirements for EAS
+----------------------------------------
+
+Energy Aware Scheduling depends on the CPUs of the system having specific
+hardware properties and on other features of the kernel being enabled. This
+section lists these dependencies and provides hints as to how they can be met.
+
+
+6.1 - Asymmetric CPU topology
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+
+As mentioned in the introduction, EAS is only supported on platforms with
+asymmetric CPU topologies for now. This requirement is checked at run-time by
+looking for the presence of the SD_ASYM_CPUCAPACITY flag when the scheduling
+domains are built.
+
+The flag is set/cleared automatically by the scheduler topology code whenever
+there are CPUs with different capacities in a root domain. The capacities of
+CPUs are provided by arch-specific code through the arch_scale_cpu_capacity()
+callback. As an example, arm and arm64 share an implementation of this callback
+which uses a combination of CPUFreq data and device-tree bindings to compute the
+capacity of CPUs (see drivers/base/arch_topology.c for more details).
+
+So, in order to use EAS on your platform your architecture must implement the
+arch_scale_cpu_capacity() callback, and some of the CPUs must have a lower
+capacity than others.
+
+Please note that EAS is not fundamentally incompatible with SMP, but no
+significant savings on SMP platforms have been observed yet. This restriction
+could be amended in the future if proven otherwise.
+
+
+6.2 - Energy Model presence
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+EAS uses the EM of a platform to estimate the impact of scheduling decisions on
+energy. So, your platform must provide power cost tables to the EM framework in
+order to make EAS start. To do so, please refer to documentation of the
+independent EM framework in Documentation/power/energy-model.txt.
+
+Please also note that the scheduling domains need to be re-built after the
+EM has been registered in order to start EAS.
+
+
+6.3 - Energy Model complexity
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The task wake-up path is very latency-sensitive. When the EM of a platform is
+too complex (too many CPUs, too many performance domains, too many performance
+states, ...), the cost of using it in the wake-up path can become prohibitive.
+The energy-aware wake-up algorithm has a complexity of:
+
+ C = Nd * (Nc + Ns)
+
+with: Nd the number of performance domains; Nc the number of CPUs; and Ns the
+total number of OPPs (ex: for two perf. domains with 4 OPPs each, Ns = 8).
+
+A complexity check is performed at the root domain level, when scheduling
+domains are built. EAS will not start on a root domain if its C happens to be
+higher than the completely arbitrary EM_MAX_COMPLEXITY threshold (2048 at the
+time of writing).
+
+If you really want to use EAS but the complexity of your platform's Energy
+Model is too high to be used with a single root domain, you're left with only
+two possible options:
+
+ 1. split your system into separate, smaller, root domains using exclusive
+ cpusets and enable EAS locally on each of them. This option has the
+ benefit to work out of the box but the drawback of preventing load
+ balance between root domains, which can result in an unbalanced system
+ overall;
+ 2. submit patches to reduce the complexity of the EAS wake-up algorithm,
+ hence enabling it to cope with larger EMs in reasonable time.
+
+
+6.4 - Schedutil governor
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+EAS tries to predict at which OPP will the CPUs be running in the close future
+in order to estimate their energy consumption. To do so, it is assumed that OPPs
+of CPUs follow their utilization.
+
+Although it is very difficult to provide hard guarantees regarding the accuracy
+of this assumption in practice (because the hardware might not do what it is
+told to do, for example), schedutil as opposed to other CPUFreq governors at
+least _requests_ frequencies calculated using the utilization signals.
+Consequently, the only sane governor to use together with EAS is schedutil,
+because it is the only one providing some degree of consistency between
+frequency requests and energy predictions.
+
+Using EAS with any other governor than schedutil is not supported.
+
+
+6.5 Scale-invariant utilization signals
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+In order to make accurate prediction across CPUs and for all performance
+states, EAS needs frequency-invariant and CPU-invariant PELT signals. These can
+be obtained using the architecture-defined arch_scale{cpu,freq}_capacity()
+callbacks.
+
+Using EAS on a platform that doesn't implement these two callbacks is not
+supported.
+
+
+6.6 Multithreading (SMT)
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+EAS in its current form is SMT unaware and is not able to leverage
+multithreaded hardware to save energy. EAS considers threads as independent
+CPUs, which can actually be counter-productive for both performance and energy.
+
+EAS on SMT is not supported.
+++ /dev/null
- =======================
- Energy Aware Scheduling
- =======================
-
-1. Introduction
----------------
-
-Energy Aware Scheduling (or EAS) gives the scheduler the ability to predict
-the impact of its decisions on the energy consumed by CPUs. EAS relies on an
-Energy Model (EM) of the CPUs to select an energy efficient CPU for each task,
-with a minimal impact on throughput. This document aims at providing an
-introduction on how EAS works, what are the main design decisions behind it, and
-details what is needed to get it to run.
-
-Before going any further, please note that at the time of writing:
-
- /!\ EAS does not support platforms with symmetric CPU topologies /!\
-
-EAS operates only on heterogeneous CPU topologies (such as Arm big.LITTLE)
-because this is where the potential for saving energy through scheduling is
-the highest.
-
-The actual EM used by EAS is _not_ maintained by the scheduler, but by a
-dedicated framework. For details about this framework and what it provides,
-please refer to its documentation (see Documentation/power/energy-model.txt).
-
-
-2. Background and Terminology
------------------------------
-
-To make it clear from the start:
- - energy = [joule] (resource like a battery on powered devices)
- - power = energy/time = [joule/second] = [watt]
-
-The goal of EAS is to minimize energy, while still getting the job done. That
-is, we want to maximize:
-
- performance [inst/s]
- --------------------
- power [W]
-
-which is equivalent to minimizing:
-
- energy [J]
- -----------
- instruction
-
-while still getting 'good' performance. It is essentially an alternative
-optimization objective to the current performance-only objective for the
-scheduler. This alternative considers two objectives: energy-efficiency and
-performance.
-
-The idea behind introducing an EM is to allow the scheduler to evaluate the
-implications of its decisions rather than blindly applying energy-saving
-techniques that may have positive effects only on some platforms. At the same
-time, the EM must be as simple as possible to minimize the scheduler latency
-impact.
-
-In short, EAS changes the way CFS tasks are assigned to CPUs. When it is time
-for the scheduler to decide where a task should run (during wake-up), the EM
-is used to break the tie between several good CPU candidates and pick the one
-that is predicted to yield the best energy consumption without harming the
-system's throughput. The predictions made by EAS rely on specific elements of
-knowledge about the platform's topology, which include the 'capacity' of CPUs,
-and their respective energy costs.
-
-
-3. Topology information
------------------------
-
-EAS (as well as the rest of the scheduler) uses the notion of 'capacity' to
-differentiate CPUs with different computing throughput. The 'capacity' of a CPU
-represents the amount of work it can absorb when running at its highest
-frequency compared to the most capable CPU of the system. Capacity values are
-normalized in a 1024 range, and are comparable with the utilization signals of
-tasks and CPUs computed by the Per-Entity Load Tracking (PELT) mechanism. Thanks
-to capacity and utilization values, EAS is able to estimate how big/busy a
-task/CPU is, and to take this into consideration when evaluating performance vs
-energy trade-offs. The capacity of CPUs is provided via arch-specific code
-through the arch_scale_cpu_capacity() callback.
-
-The rest of platform knowledge used by EAS is directly read from the Energy
-Model (EM) framework. The EM of a platform is composed of a power cost table
-per 'performance domain' in the system (see Documentation/power/energy-model.txt
-for futher details about performance domains).
-
-The scheduler manages references to the EM objects in the topology code when the
-scheduling domains are built, or re-built. For each root domain (rd), the
-scheduler maintains a singly linked list of all performance domains intersecting
-the current rd->span. Each node in the list contains a pointer to a struct
-em_perf_domain as provided by the EM framework.
-
-The lists are attached to the root domains in order to cope with exclusive
-cpuset configurations. Since the boundaries of exclusive cpusets do not
-necessarily match those of performance domains, the lists of different root
-domains can contain duplicate elements.
-
-Example 1.
- Let us consider a platform with 12 CPUs, split in 3 performance domains
- (pd0, pd4 and pd8), organized as follows:
-
- CPUs: 0 1 2 3 4 5 6 7 8 9 10 11
- PDs: |--pd0--|--pd4--|---pd8---|
- RDs: |----rd1----|-----rd2-----|
-
- Now, consider that userspace decided to split the system with two
- exclusive cpusets, hence creating two independent root domains, each
- containing 6 CPUs. The two root domains are denoted rd1 and rd2 in the
- above figure. Since pd4 intersects with both rd1 and rd2, it will be
- present in the linked list '->pd' attached to each of them:
- * rd1->pd: pd0 -> pd4
- * rd2->pd: pd4 -> pd8
-
- Please note that the scheduler will create two duplicate list nodes for
- pd4 (one for each list). However, both just hold a pointer to the same
- shared data structure of the EM framework.
-
-Since the access to these lists can happen concurrently with hotplug and other
-things, they are protected by RCU, like the rest of topology structures
-manipulated by the scheduler.
-
-EAS also maintains a static key (sched_energy_present) which is enabled when at
-least one root domain meets all conditions for EAS to start. Those conditions
-are summarized in Section 6.
-
-
-4. Energy-Aware task placement
-------------------------------
-
-EAS overrides the CFS task wake-up balancing code. It uses the EM of the
-platform and the PELT signals to choose an energy-efficient target CPU during
-wake-up balance. When EAS is enabled, select_task_rq_fair() calls
-find_energy_efficient_cpu() to do the placement decision. This function looks
-for the CPU with the highest spare capacity (CPU capacity - CPU utilization) in
-each performance domain since it is the one which will allow us to keep the
-frequency the lowest. Then, the function checks if placing the task there could
-save energy compared to leaving it on prev_cpu, i.e. the CPU where the task ran
-in its previous activation.
-
-find_energy_efficient_cpu() uses compute_energy() to estimate what will be the
-energy consumed by the system if the waking task was migrated. compute_energy()
-looks at the current utilization landscape of the CPUs and adjusts it to
-'simulate' the task migration. The EM framework provides the em_pd_energy() API
-which computes the expected energy consumption of each performance domain for
-the given utilization landscape.
-
-An example of energy-optimized task placement decision is detailed below.
-
-Example 2.
- Let us consider a (fake) platform with 2 independent performance domains
- composed of two CPUs each. CPU0 and CPU1 are little CPUs; CPU2 and CPU3
- are big.
-
- The scheduler must decide where to place a task P whose util_avg = 200
- and prev_cpu = 0.
-
- The current utilization landscape of the CPUs is depicted on the graph
- below. CPUs 0-3 have a util_avg of 400, 100, 600 and 500 respectively
- Each performance domain has three Operating Performance Points (OPPs).
- The CPU capacity and power cost associated with each OPP is listed in
- the Energy Model table. The util_avg of P is shown on the figures
- below as 'PP'.
-
- CPU util.
- 1024 - - - - - - - Energy Model
- +-----------+-------------+
- | Little | Big |
- 768 ============= +-----+-----+------+------+
- | Cap | Pwr | Cap | Pwr |
- +-----+-----+------+------+
- 512 =========== - ##- - - - - | 170 | 50 | 512 | 400 |
- ## ## | 341 | 150 | 768 | 800 |
- 341 -PP - - - - ## ## | 512 | 300 | 1024 | 1700 |
- PP ## ## +-----+-----+------+------+
- 170 -## - - - - ## ##
- ## ## ## ##
- ------------ -------------
- CPU0 CPU1 CPU2 CPU3
-
- Current OPP: ===== Other OPP: - - - util_avg (100 each): ##
-
-
- find_energy_efficient_cpu() will first look for the CPUs with the
- maximum spare capacity in the two performance domains. In this example,
- CPU1 and CPU3. Then it will estimate the energy of the system if P was
- placed on either of them, and check if that would save some energy
- compared to leaving P on CPU0. EAS assumes that OPPs follow utilization
- (which is coherent with the behaviour of the schedutil CPUFreq
- governor, see Section 6. for more details on this topic).
-
- Case 1. P is migrated to CPU1
- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
- 1024 - - - - - - -
-
- Energy calculation:
- 768 ============= * CPU0: 200 / 341 * 150 = 88
- * CPU1: 300 / 341 * 150 = 131
- * CPU2: 600 / 768 * 800 = 625
- 512 - - - - - - - ##- - - - - * CPU3: 500 / 768 * 800 = 520
- ## ## => total_energy = 1364
- 341 =========== ## ##
- PP ## ##
- 170 -## - - PP- ## ##
- ## ## ## ##
- ------------ -------------
- CPU0 CPU1 CPU2 CPU3
-
-
- Case 2. P is migrated to CPU3
- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
- 1024 - - - - - - -
-
- Energy calculation:
- 768 ============= * CPU0: 200 / 341 * 150 = 88
- * CPU1: 100 / 341 * 150 = 43
- PP * CPU2: 600 / 768 * 800 = 625
- 512 - - - - - - - ##- - -PP - * CPU3: 700 / 768 * 800 = 729
- ## ## => total_energy = 1485
- 341 =========== ## ##
- ## ##
- 170 -## - - - - ## ##
- ## ## ## ##
- ------------ -------------
- CPU0 CPU1 CPU2 CPU3
-
-
- Case 3. P stays on prev_cpu / CPU 0
- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
- 1024 - - - - - - -
-
- Energy calculation:
- 768 ============= * CPU0: 400 / 512 * 300 = 234
- * CPU1: 100 / 512 * 300 = 58
- * CPU2: 600 / 768 * 800 = 625
- 512 =========== - ##- - - - - * CPU3: 500 / 768 * 800 = 520
- ## ## => total_energy = 1437
- 341 -PP - - - - ## ##
- PP ## ##
- 170 -## - - - - ## ##
- ## ## ## ##
- ------------ -------------
- CPU0 CPU1 CPU2 CPU3
-
-
- From these calculations, the Case 1 has the lowest total energy. So CPU 1
- is be the best candidate from an energy-efficiency standpoint.
-
-Big CPUs are generally more power hungry than the little ones and are thus used
-mainly when a task doesn't fit the littles. However, little CPUs aren't always
-necessarily more energy-efficient than big CPUs. For some systems, the high OPPs
-of the little CPUs can be less energy-efficient than the lowest OPPs of the
-bigs, for example. So, if the little CPUs happen to have enough utilization at
-a specific point in time, a small task waking up at that moment could be better
-of executing on the big side in order to save energy, even though it would fit
-on the little side.
-
-And even in the case where all OPPs of the big CPUs are less energy-efficient
-than those of the little, using the big CPUs for a small task might still, under
-specific conditions, save energy. Indeed, placing a task on a little CPU can
-result in raising the OPP of the entire performance domain, and that will
-increase the cost of the tasks already running there. If the waking task is
-placed on a big CPU, its own execution cost might be higher than if it was
-running on a little, but it won't impact the other tasks of the little CPUs
-which will keep running at a lower OPP. So, when considering the total energy
-consumed by CPUs, the extra cost of running that one task on a big core can be
-smaller than the cost of raising the OPP on the little CPUs for all the other
-tasks.
-
-The examples above would be nearly impossible to get right in a generic way, and
-for all platforms, without knowing the cost of running at different OPPs on all
-CPUs of the system. Thanks to its EM-based design, EAS should cope with them
-correctly without too many troubles. However, in order to ensure a minimal
-impact on throughput for high-utilization scenarios, EAS also implements another
-mechanism called 'over-utilization'.
-
-
-5. Over-utilization
--------------------
-
-From a general standpoint, the use-cases where EAS can help the most are those
-involving a light/medium CPU utilization. Whenever long CPU-bound tasks are
-being run, they will require all of the available CPU capacity, and there isn't
-much that can be done by the scheduler to save energy without severly harming
-throughput. In order to avoid hurting performance with EAS, CPUs are flagged as
-'over-utilized' as soon as they are used at more than 80% of their compute
-capacity. As long as no CPUs are over-utilized in a root domain, load balancing
-is disabled and EAS overridess the wake-up balancing code. EAS is likely to load
-the most energy efficient CPUs of the system more than the others if that can be
-done without harming throughput. So, the load-balancer is disabled to prevent
-it from breaking the energy-efficient task placement found by EAS. It is safe to
-do so when the system isn't overutilized since being below the 80% tipping point
-implies that:
-
- a. there is some idle time on all CPUs, so the utilization signals used by
- EAS are likely to accurately represent the 'size' of the various tasks
- in the system;
- b. all tasks should already be provided with enough CPU capacity,
- regardless of their nice values;
- c. since there is spare capacity all tasks must be blocking/sleeping
- regularly and balancing at wake-up is sufficient.
-
-As soon as one CPU goes above the 80% tipping point, at least one of the three
-assumptions above becomes incorrect. In this scenario, the 'overutilized' flag
-is raised for the entire root domain, EAS is disabled, and the load-balancer is
-re-enabled. By doing so, the scheduler falls back onto load-based algorithms for
-wake-up and load balance under CPU-bound conditions. This provides a better
-respect of the nice values of tasks.
-
-Since the notion of overutilization largely relies on detecting whether or not
-there is some idle time in the system, the CPU capacity 'stolen' by higher
-(than CFS) scheduling classes (as well as IRQ) must be taken into account. As
-such, the detection of overutilization accounts for the capacity used not only
-by CFS tasks, but also by the other scheduling classes and IRQ.
-
-
-6. Dependencies and requirements for EAS
-----------------------------------------
-
-Energy Aware Scheduling depends on the CPUs of the system having specific
-hardware properties and on other features of the kernel being enabled. This
-section lists these dependencies and provides hints as to how they can be met.
-
-
- 6.1 - Asymmetric CPU topology
-
-As mentioned in the introduction, EAS is only supported on platforms with
-asymmetric CPU topologies for now. This requirement is checked at run-time by
-looking for the presence of the SD_ASYM_CPUCAPACITY flag when the scheduling
-domains are built.
-
-The flag is set/cleared automatically by the scheduler topology code whenever
-there are CPUs with different capacities in a root domain. The capacities of
-CPUs are provided by arch-specific code through the arch_scale_cpu_capacity()
-callback. As an example, arm and arm64 share an implementation of this callback
-which uses a combination of CPUFreq data and device-tree bindings to compute the
-capacity of CPUs (see drivers/base/arch_topology.c for more details).
-
-So, in order to use EAS on your platform your architecture must implement the
-arch_scale_cpu_capacity() callback, and some of the CPUs must have a lower
-capacity than others.
-
-Please note that EAS is not fundamentally incompatible with SMP, but no
-significant savings on SMP platforms have been observed yet. This restriction
-could be amended in the future if proven otherwise.
-
-
- 6.2 - Energy Model presence
-
-EAS uses the EM of a platform to estimate the impact of scheduling decisions on
-energy. So, your platform must provide power cost tables to the EM framework in
-order to make EAS start. To do so, please refer to documentation of the
-independent EM framework in Documentation/power/energy-model.txt.
-
-Please also note that the scheduling domains need to be re-built after the
-EM has been registered in order to start EAS.
-
-
- 6.3 - Energy Model complexity
-
-The task wake-up path is very latency-sensitive. When the EM of a platform is
-too complex (too many CPUs, too many performance domains, too many performance
-states, ...), the cost of using it in the wake-up path can become prohibitive.
-The energy-aware wake-up algorithm has a complexity of:
-
- C = Nd * (Nc + Ns)
-
-with: Nd the number of performance domains; Nc the number of CPUs; and Ns the
-total number of OPPs (ex: for two perf. domains with 4 OPPs each, Ns = 8).
-
-A complexity check is performed at the root domain level, when scheduling
-domains are built. EAS will not start on a root domain if its C happens to be
-higher than the completely arbitrary EM_MAX_COMPLEXITY threshold (2048 at the
-time of writing).
-
-If you really want to use EAS but the complexity of your platform's Energy
-Model is too high to be used with a single root domain, you're left with only
-two possible options:
-
- 1. split your system into separate, smaller, root domains using exclusive
- cpusets and enable EAS locally on each of them. This option has the
- benefit to work out of the box but the drawback of preventing load
- balance between root domains, which can result in an unbalanced system
- overall;
- 2. submit patches to reduce the complexity of the EAS wake-up algorithm,
- hence enabling it to cope with larger EMs in reasonable time.
-
-
- 6.4 - Schedutil governor
-
-EAS tries to predict at which OPP will the CPUs be running in the close future
-in order to estimate their energy consumption. To do so, it is assumed that OPPs
-of CPUs follow their utilization.
-
-Although it is very difficult to provide hard guarantees regarding the accuracy
-of this assumption in practice (because the hardware might not do what it is
-told to do, for example), schedutil as opposed to other CPUFreq governors at
-least _requests_ frequencies calculated using the utilization signals.
-Consequently, the only sane governor to use together with EAS is schedutil,
-because it is the only one providing some degree of consistency between
-frequency requests and energy predictions.
-
-Using EAS with any other governor than schedutil is not supported.
-
-
- 6.5 Scale-invariant utilization signals
-
-In order to make accurate prediction across CPUs and for all performance
-states, EAS needs frequency-invariant and CPU-invariant PELT signals. These can
-be obtained using the architecture-defined arch_scale{cpu,freq}_capacity()
-callbacks.
-
-Using EAS on a platform that doesn't implement these two callbacks is not
-supported.
-
-
- 6.6 Multithreading (SMT)
-
-EAS in its current form is SMT unaware and is not able to leverage
-multithreaded hardware to save energy. EAS considers threads as independent
-CPUs, which can actually be counter-productive for both performance and energy.
-
-EAS on SMT is not supported.
--- /dev/null
+=====================
+Scheduler Nice Design
+=====================
+
+This document explains the thinking about the revamped and streamlined
+nice-levels implementation in the new Linux scheduler.
+
+Nice levels were always pretty weak under Linux and people continuously
+pestered us to make nice +19 tasks use up much less CPU time.
+
+Unfortunately that was not that easy to implement under the old
+scheduler, (otherwise we'd have done it long ago) because nice level
+support was historically coupled to timeslice length, and timeslice
+units were driven by the HZ tick, so the smallest timeslice was 1/HZ.
+
+In the O(1) scheduler (in 2003) we changed negative nice levels to be
+much stronger than they were before in 2.4 (and people were happy about
+that change), and we also intentionally calibrated the linear timeslice
+rule so that nice +19 level would be _exactly_ 1 jiffy. To better
+understand it, the timeslice graph went like this (cheesy ASCII art
+alert!)::
+
+
+ A
+ \ | [timeslice length]
+ \ |
+ \ |
+ \ |
+ \ |
+ \|___100msecs
+ |^ . _
+ | ^ . _
+ | ^ . _
+ -*----------------------------------*-----> [nice level]
+ -20 | +19
+ |
+ |
+
+So that if someone wanted to really renice tasks, +19 would give a much
+bigger hit than the normal linear rule would do. (The solution of
+changing the ABI to extend priorities was discarded early on.)
+
+This approach worked to some degree for some time, but later on with
+HZ=1000 it caused 1 jiffy to be 1 msec, which meant 0.1% CPU usage which
+we felt to be a bit excessive. Excessive _not_ because it's too small of
+a CPU utilization, but because it causes too frequent (once per
+millisec) rescheduling. (and would thus trash the cache, etc. Remember,
+this was long ago when hardware was weaker and caches were smaller, and
+people were running number crunching apps at nice +19.)
+
+So for HZ=1000 we changed nice +19 to 5msecs, because that felt like the
+right minimal granularity - and this translates to 5% CPU utilization.
+But the fundamental HZ-sensitive property for nice+19 still remained,
+and we never got a single complaint about nice +19 being too _weak_ in
+terms of CPU utilization, we only got complaints about it (still) being
+too _strong_ :-)
+
+To sum it up: we always wanted to make nice levels more consistent, but
+within the constraints of HZ and jiffies and their nasty design level
+coupling to timeslices and granularity it was not really viable.
+
+The second (less frequent but still periodically occurring) complaint
+about Linux's nice level support was its assymetry around the origo
+(which you can see demonstrated in the picture above), or more
+accurately: the fact that nice level behavior depended on the _absolute_
+nice level as well, while the nice API itself is fundamentally
+"relative":
+
+ int nice(int inc);
+
+ asmlinkage long sys_nice(int increment)
+
+(the first one is the glibc API, the second one is the syscall API.)
+Note that the 'inc' is relative to the current nice level. Tools like
+bash's "nice" command mirror this relative API.
+
+With the old scheduler, if you for example started a niced task with +1
+and another task with +2, the CPU split between the two tasks would
+depend on the nice level of the parent shell - if it was at nice -10 the
+CPU split was different than if it was at +5 or +10.
+
+A third complaint against Linux's nice level support was that negative
+nice levels were not 'punchy enough', so lots of people had to resort to
+run audio (and other multimedia) apps under RT priorities such as
+SCHED_FIFO. But this caused other problems: SCHED_FIFO is not starvation
+proof, and a buggy SCHED_FIFO app can also lock up the system for good.
+
+The new scheduler in v2.6.23 addresses all three types of complaints:
+
+To address the first complaint (of nice levels being not "punchy"
+enough), the scheduler was decoupled from 'time slice' and HZ concepts
+(and granularity was made a separate concept from nice levels) and thus
+it was possible to implement better and more consistent nice +19
+support: with the new scheduler nice +19 tasks get a HZ-independent
+1.5%, instead of the variable 3%-5%-9% range they got in the old
+scheduler.
+
+To address the second complaint (of nice levels not being consistent),
+the new scheduler makes nice(1) have the same CPU utilization effect on
+tasks, regardless of their absolute nice levels. So on the new
+scheduler, running a nice +10 and a nice 11 task has the same CPU
+utilization "split" between them as running a nice -5 and a nice -4
+task. (one will get 55% of the CPU, the other 45%.) That is why nice
+levels were changed to be "multiplicative" (or exponential) - that way
+it does not matter which nice level you start out from, the 'relative
+result' will always be the same.
+
+The third complaint (of negative nice levels not being "punchy" enough
+and forcing audio apps to run under the more dangerous SCHED_FIFO
+scheduling policy) is addressed by the new scheduler almost
+automatically: stronger negative nice levels are an automatic
+side-effect of the recalibrated dynamic range of nice levels.
+++ /dev/null
-This document explains the thinking about the revamped and streamlined
-nice-levels implementation in the new Linux scheduler.
-
-Nice levels were always pretty weak under Linux and people continuously
-pestered us to make nice +19 tasks use up much less CPU time.
-
-Unfortunately that was not that easy to implement under the old
-scheduler, (otherwise we'd have done it long ago) because nice level
-support was historically coupled to timeslice length, and timeslice
-units were driven by the HZ tick, so the smallest timeslice was 1/HZ.
-
-In the O(1) scheduler (in 2003) we changed negative nice levels to be
-much stronger than they were before in 2.4 (and people were happy about
-that change), and we also intentionally calibrated the linear timeslice
-rule so that nice +19 level would be _exactly_ 1 jiffy. To better
-understand it, the timeslice graph went like this (cheesy ASCII art
-alert!):
-
-
- A
- \ | [timeslice length]
- \ |
- \ |
- \ |
- \ |
- \|___100msecs
- |^ . _
- | ^ . _
- | ^ . _
- -*----------------------------------*-----> [nice level]
- -20 | +19
- |
- |
-
-So that if someone wanted to really renice tasks, +19 would give a much
-bigger hit than the normal linear rule would do. (The solution of
-changing the ABI to extend priorities was discarded early on.)
-
-This approach worked to some degree for some time, but later on with
-HZ=1000 it caused 1 jiffy to be 1 msec, which meant 0.1% CPU usage which
-we felt to be a bit excessive. Excessive _not_ because it's too small of
-a CPU utilization, but because it causes too frequent (once per
-millisec) rescheduling. (and would thus trash the cache, etc. Remember,
-this was long ago when hardware was weaker and caches were smaller, and
-people were running number crunching apps at nice +19.)
-
-So for HZ=1000 we changed nice +19 to 5msecs, because that felt like the
-right minimal granularity - and this translates to 5% CPU utilization.
-But the fundamental HZ-sensitive property for nice+19 still remained,
-and we never got a single complaint about nice +19 being too _weak_ in
-terms of CPU utilization, we only got complaints about it (still) being
-too _strong_ :-)
-
-To sum it up: we always wanted to make nice levels more consistent, but
-within the constraints of HZ and jiffies and their nasty design level
-coupling to timeslices and granularity it was not really viable.
-
-The second (less frequent but still periodically occurring) complaint
-about Linux's nice level support was its assymetry around the origo
-(which you can see demonstrated in the picture above), or more
-accurately: the fact that nice level behavior depended on the _absolute_
-nice level as well, while the nice API itself is fundamentally
-"relative":
-
- int nice(int inc);
-
- asmlinkage long sys_nice(int increment)
-
-(the first one is the glibc API, the second one is the syscall API.)
-Note that the 'inc' is relative to the current nice level. Tools like
-bash's "nice" command mirror this relative API.
-
-With the old scheduler, if you for example started a niced task with +1
-and another task with +2, the CPU split between the two tasks would
-depend on the nice level of the parent shell - if it was at nice -10 the
-CPU split was different than if it was at +5 or +10.
-
-A third complaint against Linux's nice level support was that negative
-nice levels were not 'punchy enough', so lots of people had to resort to
-run audio (and other multimedia) apps under RT priorities such as
-SCHED_FIFO. But this caused other problems: SCHED_FIFO is not starvation
-proof, and a buggy SCHED_FIFO app can also lock up the system for good.
-
-The new scheduler in v2.6.23 addresses all three types of complaints:
-
-To address the first complaint (of nice levels being not "punchy"
-enough), the scheduler was decoupled from 'time slice' and HZ concepts
-(and granularity was made a separate concept from nice levels) and thus
-it was possible to implement better and more consistent nice +19
-support: with the new scheduler nice +19 tasks get a HZ-independent
-1.5%, instead of the variable 3%-5%-9% range they got in the old
-scheduler.
-
-To address the second complaint (of nice levels not being consistent),
-the new scheduler makes nice(1) have the same CPU utilization effect on
-tasks, regardless of their absolute nice levels. So on the new
-scheduler, running a nice +10 and a nice 11 task has the same CPU
-utilization "split" between them as running a nice -5 and a nice -4
-task. (one will get 55% of the CPU, the other 45%.) That is why nice
-levels were changed to be "multiplicative" (or exponential) - that way
-it does not matter which nice level you start out from, the 'relative
-result' will always be the same.
-
-The third complaint (of negative nice levels not being "punchy" enough
-and forcing audio apps to run under the more dangerous SCHED_FIFO
-scheduling policy) is addressed by the new scheduler almost
-automatically: stronger negative nice levels are an automatic
-side-effect of the recalibrated dynamic range of nice levels.
--- /dev/null
+==========================
+Real-Time group scheduling
+==========================
+
+.. CONTENTS
+
+ 0. WARNING
+ 1. Overview
+ 1.1 The problem
+ 1.2 The solution
+ 2. The interface
+ 2.1 System-wide settings
+ 2.2 Default behaviour
+ 2.3 Basis for grouping tasks
+ 3. Future plans
+
+
+0. WARNING
+==========
+
+ Fiddling with these settings can result in an unstable system, the knobs are
+ root only and assumes root knows what he is doing.
+
+Most notable:
+
+ * very small values in sched_rt_period_us can result in an unstable
+ system when the period is smaller than either the available hrtimer
+ resolution, or the time it takes to handle the budget refresh itself.
+
+ * very small values in sched_rt_runtime_us can result in an unstable
+ system when the runtime is so small the system has difficulty making
+ forward progress (NOTE: the migration thread and kstopmachine both
+ are real-time processes).
+
+1. Overview
+===========
+
+
+1.1 The problem
+---------------
+
+Realtime scheduling is all about determinism, a group has to be able to rely on
+the amount of bandwidth (eg. CPU time) being constant. In order to schedule
+multiple groups of realtime tasks, each group must be assigned a fixed portion
+of the CPU time available. Without a minimum guarantee a realtime group can
+obviously fall short. A fuzzy upper limit is of no use since it cannot be
+relied upon. Which leaves us with just the single fixed portion.
+
+1.2 The solution
+----------------
+
+CPU time is divided by means of specifying how much time can be spent running
+in a given period. We allocate this "run time" for each realtime group which
+the other realtime groups will not be permitted to use.
+
+Any time not allocated to a realtime group will be used to run normal priority
+tasks (SCHED_OTHER). Any allocated run time not used will also be picked up by
+SCHED_OTHER.
+
+Let's consider an example: a frame fixed realtime renderer must deliver 25
+frames a second, which yields a period of 0.04s per frame. Now say it will also
+have to play some music and respond to input, leaving it with around 80% CPU
+time dedicated for the graphics. We can then give this group a run time of 0.8
+* 0.04s = 0.032s.
+
+This way the graphics group will have a 0.04s period with a 0.032s run time
+limit. Now if the audio thread needs to refill the DMA buffer every 0.005s, but
+needs only about 3% CPU time to do so, it can do with a 0.03 * 0.005s =
+0.00015s. So this group can be scheduled with a period of 0.005s and a run time
+of 0.00015s.
+
+The remaining CPU time will be used for user input and other tasks. Because
+realtime tasks have explicitly allocated the CPU time they need to perform
+their tasks, buffer underruns in the graphics or audio can be eliminated.
+
+NOTE: the above example is not fully implemented yet. We still
+lack an EDF scheduler to make non-uniform periods usable.
+
+
+2. The Interface
+================
+
+
+2.1 System wide settings
+------------------------
+
+The system wide settings are configured under the /proc virtual file system:
+
+/proc/sys/kernel/sched_rt_period_us:
+ The scheduling period that is equivalent to 100% CPU bandwidth
+
+/proc/sys/kernel/sched_rt_runtime_us:
+ A global limit on how much time realtime scheduling may use. Even without
+ CONFIG_RT_GROUP_SCHED enabled, this will limit time reserved to realtime
+ processes. With CONFIG_RT_GROUP_SCHED it signifies the total bandwidth
+ available to all realtime groups.
+
+ * Time is specified in us because the interface is s32. This gives an
+ operating range from 1us to about 35 minutes.
+ * sched_rt_period_us takes values from 1 to INT_MAX.
+ * sched_rt_runtime_us takes values from -1 to (INT_MAX - 1).
+ * A run time of -1 specifies runtime == period, ie. no limit.
+
+
+2.2 Default behaviour
+---------------------
+
+The default values for sched_rt_period_us (1000000 or 1s) and
+sched_rt_runtime_us (950000 or 0.95s). This gives 0.05s to be used by
+SCHED_OTHER (non-RT tasks). These defaults were chosen so that a run-away
+realtime tasks will not lock up the machine but leave a little time to recover
+it. By setting runtime to -1 you'd get the old behaviour back.
+
+By default all bandwidth is assigned to the root group and new groups get the
+period from /proc/sys/kernel/sched_rt_period_us and a run time of 0. If you
+want to assign bandwidth to another group, reduce the root group's bandwidth
+and assign some or all of the difference to another group.
+
+Realtime group scheduling means you have to assign a portion of total CPU
+bandwidth to the group before it will accept realtime tasks. Therefore you will
+not be able to run realtime tasks as any user other than root until you have
+done that, even if the user has the rights to run processes with realtime
+priority!
+
+
+2.3 Basis for grouping tasks
+----------------------------
+
+Enabling CONFIG_RT_GROUP_SCHED lets you explicitly allocate real
+CPU bandwidth to task groups.
+
+This uses the cgroup virtual file system and "<cgroup>/cpu.rt_runtime_us"
+to control the CPU time reserved for each control group.
+
+For more information on working with control groups, you should read
+Documentation/cgroup-v1/cgroups.txt as well.
+
+Group settings are checked against the following limits in order to keep the
+configuration schedulable:
+
+ \Sum_{i} runtime_{i} / global_period <= global_runtime / global_period
+
+For now, this can be simplified to just the following (but see Future plans):
+
+ \Sum_{i} runtime_{i} <= global_runtime
+
+
+3. Future plans
+===============
+
+There is work in progress to make the scheduling period for each group
+("<cgroup>/cpu.rt_period_us") configurable as well.
+
+The constraint on the period is that a subgroup must have a smaller or
+equal period to its parent. But realistically its not very useful _yet_
+as its prone to starvation without deadline scheduling.
+
+Consider two sibling groups A and B; both have 50% bandwidth, but A's
+period is twice the length of B's.
+
+* group A: period=100000us, runtime=50000us
+
+ - this runs for 0.05s once every 0.1s
+
+* group B: period= 50000us, runtime=25000us
+
+ - this runs for 0.025s twice every 0.1s (or once every 0.05 sec).
+
+This means that currently a while (1) loop in A will run for the full period of
+B and can starve B's tasks (assuming they are of lower priority) for a whole
+period.
+
+The next project will be SCHED_EDF (Earliest Deadline First scheduling) to bring
+full deadline scheduling to the linux kernel. Deadline scheduling the above
+groups and treating end of the period as a deadline will ensure that they both
+get their allocated time.
+
+Implementing SCHED_EDF might take a while to complete. Priority Inheritance is
+the biggest challenge as the current linux PI infrastructure is geared towards
+the limited static priority levels 0-99. With deadline scheduling you need to
+do deadline inheritance (since priority is inversely proportional to the
+deadline delta (deadline - now)).
+
+This means the whole PI machinery will have to be reworked - and that is one of
+the most complex pieces of code we have.
+++ /dev/null
- Real-Time group scheduling
- --------------------------
-
-CONTENTS
-========
-
-0. WARNING
-1. Overview
- 1.1 The problem
- 1.2 The solution
-2. The interface
- 2.1 System-wide settings
- 2.2 Default behaviour
- 2.3 Basis for grouping tasks
-3. Future plans
-
-
-0. WARNING
-==========
-
- Fiddling with these settings can result in an unstable system, the knobs are
- root only and assumes root knows what he is doing.
-
-Most notable:
-
- * very small values in sched_rt_period_us can result in an unstable
- system when the period is smaller than either the available hrtimer
- resolution, or the time it takes to handle the budget refresh itself.
-
- * very small values in sched_rt_runtime_us can result in an unstable
- system when the runtime is so small the system has difficulty making
- forward progress (NOTE: the migration thread and kstopmachine both
- are real-time processes).
-
-1. Overview
-===========
-
-
-1.1 The problem
----------------
-
-Realtime scheduling is all about determinism, a group has to be able to rely on
-the amount of bandwidth (eg. CPU time) being constant. In order to schedule
-multiple groups of realtime tasks, each group must be assigned a fixed portion
-of the CPU time available. Without a minimum guarantee a realtime group can
-obviously fall short. A fuzzy upper limit is of no use since it cannot be
-relied upon. Which leaves us with just the single fixed portion.
-
-1.2 The solution
-----------------
-
-CPU time is divided by means of specifying how much time can be spent running
-in a given period. We allocate this "run time" for each realtime group which
-the other realtime groups will not be permitted to use.
-
-Any time not allocated to a realtime group will be used to run normal priority
-tasks (SCHED_OTHER). Any allocated run time not used will also be picked up by
-SCHED_OTHER.
-
-Let's consider an example: a frame fixed realtime renderer must deliver 25
-frames a second, which yields a period of 0.04s per frame. Now say it will also
-have to play some music and respond to input, leaving it with around 80% CPU
-time dedicated for the graphics. We can then give this group a run time of 0.8
-* 0.04s = 0.032s.
-
-This way the graphics group will have a 0.04s period with a 0.032s run time
-limit. Now if the audio thread needs to refill the DMA buffer every 0.005s, but
-needs only about 3% CPU time to do so, it can do with a 0.03 * 0.005s =
-0.00015s. So this group can be scheduled with a period of 0.005s and a run time
-of 0.00015s.
-
-The remaining CPU time will be used for user input and other tasks. Because
-realtime tasks have explicitly allocated the CPU time they need to perform
-their tasks, buffer underruns in the graphics or audio can be eliminated.
-
-NOTE: the above example is not fully implemented yet. We still
-lack an EDF scheduler to make non-uniform periods usable.
-
-
-2. The Interface
-================
-
-
-2.1 System wide settings
-------------------------
-
-The system wide settings are configured under the /proc virtual file system:
-
-/proc/sys/kernel/sched_rt_period_us:
- The scheduling period that is equivalent to 100% CPU bandwidth
-
-/proc/sys/kernel/sched_rt_runtime_us:
- A global limit on how much time realtime scheduling may use. Even without
- CONFIG_RT_GROUP_SCHED enabled, this will limit time reserved to realtime
- processes. With CONFIG_RT_GROUP_SCHED it signifies the total bandwidth
- available to all realtime groups.
-
- * Time is specified in us because the interface is s32. This gives an
- operating range from 1us to about 35 minutes.
- * sched_rt_period_us takes values from 1 to INT_MAX.
- * sched_rt_runtime_us takes values from -1 to (INT_MAX - 1).
- * A run time of -1 specifies runtime == period, ie. no limit.
-
-
-2.2 Default behaviour
----------------------
-
-The default values for sched_rt_period_us (1000000 or 1s) and
-sched_rt_runtime_us (950000 or 0.95s). This gives 0.05s to be used by
-SCHED_OTHER (non-RT tasks). These defaults were chosen so that a run-away
-realtime tasks will not lock up the machine but leave a little time to recover
-it. By setting runtime to -1 you'd get the old behaviour back.
-
-By default all bandwidth is assigned to the root group and new groups get the
-period from /proc/sys/kernel/sched_rt_period_us and a run time of 0. If you
-want to assign bandwidth to another group, reduce the root group's bandwidth
-and assign some or all of the difference to another group.
-
-Realtime group scheduling means you have to assign a portion of total CPU
-bandwidth to the group before it will accept realtime tasks. Therefore you will
-not be able to run realtime tasks as any user other than root until you have
-done that, even if the user has the rights to run processes with realtime
-priority!
-
-
-2.3 Basis for grouping tasks
-----------------------------
-
-Enabling CONFIG_RT_GROUP_SCHED lets you explicitly allocate real
-CPU bandwidth to task groups.
-
-This uses the cgroup virtual file system and "<cgroup>/cpu.rt_runtime_us"
-to control the CPU time reserved for each control group.
-
-For more information on working with control groups, you should read
-Documentation/cgroup-v1/cgroups.txt as well.
-
-Group settings are checked against the following limits in order to keep the
-configuration schedulable:
-
- \Sum_{i} runtime_{i} / global_period <= global_runtime / global_period
-
-For now, this can be simplified to just the following (but see Future plans):
-
- \Sum_{i} runtime_{i} <= global_runtime
-
-
-3. Future plans
-===============
-
-There is work in progress to make the scheduling period for each group
-("<cgroup>/cpu.rt_period_us") configurable as well.
-
-The constraint on the period is that a subgroup must have a smaller or
-equal period to its parent. But realistically its not very useful _yet_
-as its prone to starvation without deadline scheduling.
-
-Consider two sibling groups A and B; both have 50% bandwidth, but A's
-period is twice the length of B's.
-
-* group A: period=100000us, runtime=50000us
- - this runs for 0.05s once every 0.1s
-
-* group B: period= 50000us, runtime=25000us
- - this runs for 0.025s twice every 0.1s (or once every 0.05 sec).
-
-This means that currently a while (1) loop in A will run for the full period of
-B and can starve B's tasks (assuming they are of lower priority) for a whole
-period.
-
-The next project will be SCHED_EDF (Earliest Deadline First scheduling) to bring
-full deadline scheduling to the linux kernel. Deadline scheduling the above
-groups and treating end of the period as a deadline will ensure that they both
-get their allocated time.
-
-Implementing SCHED_EDF might take a while to complete. Priority Inheritance is
-the biggest challenge as the current linux PI infrastructure is geared towards
-the limited static priority levels 0-99. With deadline scheduling you need to
-do deadline inheritance (since priority is inversely proportional to the
-deadline delta (deadline - now)).
-
-This means the whole PI machinery will have to be reworked - and that is one of
-the most complex pieces of code we have.
--- /dev/null
+====================
+Scheduler Statistics
+====================
+
+Version 15 of schedstats dropped counters for some sched_yield:
+yld_exp_empty, yld_act_empty and yld_both_empty. Otherwise, it is
+identical to version 14.
+
+Version 14 of schedstats includes support for sched_domains, which hit the
+mainline kernel in 2.6.20 although it is identical to the stats from version
+12 which was in the kernel from 2.6.13-2.6.19 (version 13 never saw a kernel
+release). Some counters make more sense to be per-runqueue; other to be
+per-domain. Note that domains (and their associated information) will only
+be pertinent and available on machines utilizing CONFIG_SMP.
+
+In version 14 of schedstat, there is at least one level of domain
+statistics for each cpu listed, and there may well be more than one
+domain. Domains have no particular names in this implementation, but
+the highest numbered one typically arbitrates balancing across all the
+cpus on the machine, while domain0 is the most tightly focused domain,
+sometimes balancing only between pairs of cpus. At this time, there
+are no architectures which need more than three domain levels. The first
+field in the domain stats is a bit map indicating which cpus are affected
+by that domain.
+
+These fields are counters, and only increment. Programs which make use
+of these will need to start with a baseline observation and then calculate
+the change in the counters at each subsequent observation. A perl script
+which does this for many of the fields is available at
+
+ http://eaglet.rain.com/rick/linux/schedstat/
+
+Note that any such script will necessarily be version-specific, as the main
+reason to change versions is changes in the output format. For those wishing
+to write their own scripts, the fields are described here.
+
+CPU statistics
+--------------
+cpu<N> 1 2 3 4 5 6 7 8 9
+
+First field is a sched_yield() statistic:
+
+ 1) # of times sched_yield() was called
+
+Next three are schedule() statistics:
+
+ 2) This field is a legacy array expiration count field used in the O(1)
+ scheduler. We kept it for ABI compatibility, but it is always set to zero.
+ 3) # of times schedule() was called
+ 4) # of times schedule() left the processor idle
+
+Next two are try_to_wake_up() statistics:
+
+ 5) # of times try_to_wake_up() was called
+ 6) # of times try_to_wake_up() was called to wake up the local cpu
+
+Next three are statistics describing scheduling latency:
+
+ 7) sum of all time spent running by tasks on this processor (in jiffies)
+ 8) sum of all time spent waiting to run by tasks on this processor (in
+ jiffies)
+ 9) # of timeslices run on this cpu
+
+
+Domain statistics
+-----------------
+One of these is produced per domain for each cpu described. (Note that if
+CONFIG_SMP is not defined, *no* domains are utilized and these lines
+will not appear in the output.)
+
+domain<N> <cpumask> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
+
+The first field is a bit mask indicating what cpus this domain operates over.
+
+The next 24 are a variety of load_balance() statistics in grouped into types
+of idleness (idle, busy, and newly idle):
+
+ 1) # of times in this domain load_balance() was called when the
+ cpu was idle
+ 2) # of times in this domain load_balance() checked but found
+ the load did not require balancing when the cpu was idle
+ 3) # of times in this domain load_balance() tried to move one or
+ more tasks and failed, when the cpu was idle
+ 4) sum of imbalances discovered (if any) with each call to
+ load_balance() in this domain when the cpu was idle
+ 5) # of times in this domain pull_task() was called when the cpu
+ was idle
+ 6) # of times in this domain pull_task() was called even though
+ the target task was cache-hot when idle
+ 7) # of times in this domain load_balance() was called but did
+ not find a busier queue while the cpu was idle
+ 8) # of times in this domain a busier queue was found while the
+ cpu was idle but no busier group was found
+ 9) # of times in this domain load_balance() was called when the
+ cpu was busy
+ 10) # of times in this domain load_balance() checked but found the
+ load did not require balancing when busy
+ 11) # of times in this domain load_balance() tried to move one or
+ more tasks and failed, when the cpu was busy
+ 12) sum of imbalances discovered (if any) with each call to
+ load_balance() in this domain when the cpu was busy
+ 13) # of times in this domain pull_task() was called when busy
+ 14) # of times in this domain pull_task() was called even though the
+ target task was cache-hot when busy
+ 15) # of times in this domain load_balance() was called but did not
+ find a busier queue while the cpu was busy
+ 16) # of times in this domain a busier queue was found while the cpu
+ was busy but no busier group was found
+
+ 17) # of times in this domain load_balance() was called when the
+ cpu was just becoming idle
+ 18) # of times in this domain load_balance() checked but found the
+ load did not require balancing when the cpu was just becoming idle
+ 19) # of times in this domain load_balance() tried to move one or more
+ tasks and failed, when the cpu was just becoming idle
+ 20) sum of imbalances discovered (if any) with each call to
+ load_balance() in this domain when the cpu was just becoming idle
+ 21) # of times in this domain pull_task() was called when newly idle
+ 22) # of times in this domain pull_task() was called even though the
+ target task was cache-hot when just becoming idle
+ 23) # of times in this domain load_balance() was called but did not
+ find a busier queue while the cpu was just becoming idle
+ 24) # of times in this domain a busier queue was found while the cpu
+ was just becoming idle but no busier group was found
+
+ Next three are active_load_balance() statistics:
+
+ 25) # of times active_load_balance() was called
+ 26) # of times active_load_balance() tried to move a task and failed
+ 27) # of times active_load_balance() successfully moved a task
+
+ Next three are sched_balance_exec() statistics:
+
+ 28) sbe_cnt is not used
+ 29) sbe_balanced is not used
+ 30) sbe_pushed is not used
+
+ Next three are sched_balance_fork() statistics:
+
+ 31) sbf_cnt is not used
+ 32) sbf_balanced is not used
+ 33) sbf_pushed is not used
+
+ Next three are try_to_wake_up() statistics:
+
+ 34) # of times in this domain try_to_wake_up() awoke a task that
+ last ran on a different cpu in this domain
+ 35) # of times in this domain try_to_wake_up() moved a task to the
+ waking cpu because it was cache-cold on its own cpu anyway
+ 36) # of times in this domain try_to_wake_up() started passive balancing
+
+/proc/<pid>/schedstat
+---------------------
+schedstats also adds a new /proc/<pid>/schedstat file to include some of
+the same information on a per-process level. There are three fields in
+this file correlating for that process to:
+
+ 1) time spent on the cpu
+ 2) time spent waiting on a runqueue
+ 3) # of timeslices run on this cpu
+
+A program could be easily written to make use of these extra fields to
+report on how well a particular process or set of processes is faring
+under the scheduler's policies. A simple version of such a program is
+available at
+
+ http://eaglet.rain.com/rick/linux/schedstat/v12/latency.c
+++ /dev/null
-Version 15 of schedstats dropped counters for some sched_yield:
-yld_exp_empty, yld_act_empty and yld_both_empty. Otherwise, it is
-identical to version 14.
-
-Version 14 of schedstats includes support for sched_domains, which hit the
-mainline kernel in 2.6.20 although it is identical to the stats from version
-12 which was in the kernel from 2.6.13-2.6.19 (version 13 never saw a kernel
-release). Some counters make more sense to be per-runqueue; other to be
-per-domain. Note that domains (and their associated information) will only
-be pertinent and available on machines utilizing CONFIG_SMP.
-
-In version 14 of schedstat, there is at least one level of domain
-statistics for each cpu listed, and there may well be more than one
-domain. Domains have no particular names in this implementation, but
-the highest numbered one typically arbitrates balancing across all the
-cpus on the machine, while domain0 is the most tightly focused domain,
-sometimes balancing only between pairs of cpus. At this time, there
-are no architectures which need more than three domain levels. The first
-field in the domain stats is a bit map indicating which cpus are affected
-by that domain.
-
-These fields are counters, and only increment. Programs which make use
-of these will need to start with a baseline observation and then calculate
-the change in the counters at each subsequent observation. A perl script
-which does this for many of the fields is available at
-
- http://eaglet.rain.com/rick/linux/schedstat/
-
-Note that any such script will necessarily be version-specific, as the main
-reason to change versions is changes in the output format. For those wishing
-to write their own scripts, the fields are described here.
-
-CPU statistics
---------------
-cpu<N> 1 2 3 4 5 6 7 8 9
-
-First field is a sched_yield() statistic:
- 1) # of times sched_yield() was called
-
-Next three are schedule() statistics:
- 2) This field is a legacy array expiration count field used in the O(1)
- scheduler. We kept it for ABI compatibility, but it is always set to zero.
- 3) # of times schedule() was called
- 4) # of times schedule() left the processor idle
-
-Next two are try_to_wake_up() statistics:
- 5) # of times try_to_wake_up() was called
- 6) # of times try_to_wake_up() was called to wake up the local cpu
-
-Next three are statistics describing scheduling latency:
- 7) sum of all time spent running by tasks on this processor (in jiffies)
- 8) sum of all time spent waiting to run by tasks on this processor (in
- jiffies)
- 9) # of timeslices run on this cpu
-
-
-Domain statistics
------------------
-One of these is produced per domain for each cpu described. (Note that if
-CONFIG_SMP is not defined, *no* domains are utilized and these lines
-will not appear in the output.)
-
-domain<N> <cpumask> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
-
-The first field is a bit mask indicating what cpus this domain operates over.
-
-The next 24 are a variety of load_balance() statistics in grouped into types
-of idleness (idle, busy, and newly idle):
-
- 1) # of times in this domain load_balance() was called when the
- cpu was idle
- 2) # of times in this domain load_balance() checked but found
- the load did not require balancing when the cpu was idle
- 3) # of times in this domain load_balance() tried to move one or
- more tasks and failed, when the cpu was idle
- 4) sum of imbalances discovered (if any) with each call to
- load_balance() in this domain when the cpu was idle
- 5) # of times in this domain pull_task() was called when the cpu
- was idle
- 6) # of times in this domain pull_task() was called even though
- the target task was cache-hot when idle
- 7) # of times in this domain load_balance() was called but did
- not find a busier queue while the cpu was idle
- 8) # of times in this domain a busier queue was found while the
- cpu was idle but no busier group was found
-
- 9) # of times in this domain load_balance() was called when the
- cpu was busy
- 10) # of times in this domain load_balance() checked but found the
- load did not require balancing when busy
- 11) # of times in this domain load_balance() tried to move one or
- more tasks and failed, when the cpu was busy
- 12) sum of imbalances discovered (if any) with each call to
- load_balance() in this domain when the cpu was busy
- 13) # of times in this domain pull_task() was called when busy
- 14) # of times in this domain pull_task() was called even though the
- target task was cache-hot when busy
- 15) # of times in this domain load_balance() was called but did not
- find a busier queue while the cpu was busy
- 16) # of times in this domain a busier queue was found while the cpu
- was busy but no busier group was found
-
- 17) # of times in this domain load_balance() was called when the
- cpu was just becoming idle
- 18) # of times in this domain load_balance() checked but found the
- load did not require balancing when the cpu was just becoming idle
- 19) # of times in this domain load_balance() tried to move one or more
- tasks and failed, when the cpu was just becoming idle
- 20) sum of imbalances discovered (if any) with each call to
- load_balance() in this domain when the cpu was just becoming idle
- 21) # of times in this domain pull_task() was called when newly idle
- 22) # of times in this domain pull_task() was called even though the
- target task was cache-hot when just becoming idle
- 23) # of times in this domain load_balance() was called but did not
- find a busier queue while the cpu was just becoming idle
- 24) # of times in this domain a busier queue was found while the cpu
- was just becoming idle but no busier group was found
-
- Next three are active_load_balance() statistics:
- 25) # of times active_load_balance() was called
- 26) # of times active_load_balance() tried to move a task and failed
- 27) # of times active_load_balance() successfully moved a task
-
- Next three are sched_balance_exec() statistics:
- 28) sbe_cnt is not used
- 29) sbe_balanced is not used
- 30) sbe_pushed is not used
-
- Next three are sched_balance_fork() statistics:
- 31) sbf_cnt is not used
- 32) sbf_balanced is not used
- 33) sbf_pushed is not used
-
- Next three are try_to_wake_up() statistics:
- 34) # of times in this domain try_to_wake_up() awoke a task that
- last ran on a different cpu in this domain
- 35) # of times in this domain try_to_wake_up() moved a task to the
- waking cpu because it was cache-cold on its own cpu anyway
- 36) # of times in this domain try_to_wake_up() started passive balancing
-
-/proc/<pid>/schedstat
-----------------
-schedstats also adds a new /proc/<pid>/schedstat file to include some of
-the same information on a per-process level. There are three fields in
-this file correlating for that process to:
- 1) time spent on the cpu
- 2) time spent waiting on a runqueue
- 3) # of timeslices run on this cpu
-
-A program could be easily written to make use of these extra fields to
-report on how well a particular process or set of processes is faring
-under the scheduler's policies. A simple version of such a program is
-available at
- http://eaglet.rain.com/rick/linux/schedstat/v12/latency.c
--- /dev/null
+Scheduler pelt c program
+------------------------
+
+.. literalinclude:: sched-pelt.c
+ :language: c
as long as the task on whose behalf the kernel allocated some memory does not
later migrate away from that memory. The Linux scheduler is aware of the
NUMA topology of the platform--embodied in the "scheduling domains" data
-structures [see Documentation/scheduler/sched-domains.txt]--and the scheduler
+structures [see Documentation/scheduler/sched-domains.rst]--and the scheduler
attempts to minimize task migration to distant scheduling domains. However,
the scheduler does not take a task's NUMA footprint into account directly.
Thus, under sufficient imbalance, tasks can migrate between nodes, remote
use with process control subsystems such as Cpusets, CFS, memory
controls or device isolation.
See
- - Documentation/scheduler/sched-design-CFS.txt (CFS)
+ - Documentation/scheduler/sched-design-CFS.rst (CFS)
- Documentation/cgroup-v1/ (features for grouping, isolation
and resource control)
tasks running within the fair group scheduler. Groups with no limit
set are considered to be unconstrained and will run with no
restriction.
- See Documentation/scheduler/sched-bwc.txt for more information.
+ See Documentation/scheduler/sched-bwc.rst for more information.
config RT_GROUP_SCHED
bool "Group scheduling for SCHED_RR/FIFO"
to task groups. If enabled, it will also make it impossible to
schedule realtime tasks for non-root users until you allocate
realtime bandwidth for them.
- See Documentation/scheduler/sched-rt-group.txt for more information.
+ See Documentation/scheduler/sched-rt-group.rst for more information.
endif #CGROUP_SCHED
* refill the runtime and set the deadline a period in the future,
* because keeping the current (absolute) deadline of the task would
* result in breaking guarantees promised to other tasks (refer to
- * Documentation/scheduler/sched-deadline.txt for more information).
+ * Documentation/scheduler/sched-deadline.rst for more information).
*
* This function returns true if:
*
projects / openwrt / staging / blogic.git / commitdiff