Extrapolating on the existing framework to track rt/dl utilization using
pelt signals, add a similar mechanism to track thermal pressure. The
difference here from rt/dl utilization tracking is that, instead of
tracking time spent by a CPU running a RT/DL task through util_avg, the
average thermal pressure is tracked through load_avg. This is because
thermal pressure signal is weighted time "delta" capacity unlike util_avg
which is binary. "delta capacity" here means delta between the actual
capacity of a CPU and the decreased capacity a CPU due to a thermal event.
In order to track average thermal pressure, a new sched_avg variable
avg_thermal is introduced. Function update_thermal_load_avg can be called
to do the periodic bookkeeping (accumulate, decay and average) of the
thermal pressure.
Reviewed-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Thara Gopinath <thara.gopinath@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Link: https://lkml.kernel.org/r/20200222005213.3873-2-thara.gopinath@linaro.org
Signed-off-by: Divyanshu-Modi <divyan.m05@gmail.com>
Signed-off-by: Helium-Studio <67852324+Helium-Studio@users.noreply.github.com>
Extrapolating on the existing framework to track rt/dl utilization using
pelt signals, add a similar mechanism to track thermal pressure. The
difference here from rt/dl utilization tracking is that, instead of
tracking time spent by a CPU running a RT/DL task through util_avg, the
average thermal pressure is tracked through load_avg. This is because
thermal pressure signal is weighted time "delta" capacity unlike util_avg
which is binary. "delta capacity" here means delta between the actual
capacity of a CPU and the decreased capacity a CPU due to a thermal event.
In order to track average thermal pressure, a new sched_avg variable
avg_thermal is introduced. Function update_thermal_load_avg can be called
to do the periodic bookkeeping (accumulate, decay and average) of the
thermal pressure.
Reviewed-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Thara Gopinath <thara.gopinath@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Link: https://lkml.kernel.org/r/20200222005213.3873-2-thara.gopinath@linaro.org
Extrapolating on the existing framework to track rt/dl utilization using
pelt signals, add a similar mechanism to track thermal pressure. The
difference here from rt/dl utilization tracking is that, instead of
tracking time spent by a CPU running a RT/DL task through util_avg, the
average thermal pressure is tracked through load_avg. This is because
thermal pressure signal is weighted time "delta" capacity unlike util_avg
which is binary. "delta capacity" here means delta between the actual
capacity of a CPU and the decreased capacity a CPU due to a thermal event.
In order to track average thermal pressure, a new sched_avg variable
avg_thermal is introduced. Function update_thermal_load_avg can be called
to do the periodic bookkeeping (accumulate, decay and average) of the
thermal pressure.
Reviewed-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Thara Gopinath <thara.gopinath@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Link: https://lkml.kernel.org/r/20200222005213.3873-2-thara.gopinath@linaro.org
Extrapolating on the existing framework to track rt/dl utilization using
pelt signals, add a similar mechanism to track thermal pressure. The
difference here from rt/dl utilization tracking is that, instead of
tracking time spent by a CPU running a RT/DL task through util_avg, the
average thermal pressure is tracked through load_avg. This is because
thermal pressure signal is weighted time "delta" capacity unlike util_avg
which is binary. "delta capacity" here means delta between the actual
capacity of a CPU and the decreased capacity a CPU due to a thermal event.
In order to track average thermal pressure, a new sched_avg variable
avg_thermal is introduced. Function update_thermal_load_avg can be called
to do the periodic bookkeeping (accumulate, decay and average) of the
thermal pressure.
Reviewed-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Thara Gopinath <thara.gopinath@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Link: https://lkml.kernel.org/r/20200222005213.3873-2-thara.gopinath@linaro.org
The Capacity Aware Superset Scheduler (CASS) optimizes runqueue selection
of CFS tasks. By using CPU capacity as a basis for comparing the relative
utilization between different CPUs, CASS fairly balances load across CPUs
of varying capacities. This results in improved multi-core performance,
especially when CPUs are overutilized because CASS doesn't clip a CPU's
utilization when it eclipses the CPU's capacity.
As a superset of capacity aware scheduling, CASS implements a hierarchy of
criteria to determine the better CPU to wake a task upon between CPUs that
have the same relative utilization. This way, single-core performance,
latency, and cache affinity are all optimized where possible.
CASS doesn't feature explicit energy awareness but its basic load balancing
principle results in decreased overall energy, often better than what is
possible with explicit energy awareness. By fairly balancing load based on
relative utilization, all CPUs are kept at their lowest P-state necessary
to satisfy the overall load at any given moment.
Signed-off-by: Sultan Alsawaf <sultan@kerneltoast.com>
commit 9df9d2f0471b4c4702670380b8d8a45b40b23a7d upstream
X86 is reworking the boot process so that initializations which are not
required during early boot can be moved into the late boot process and out
of the fragile and restricted initial boot phase.
arch_cpu_finalize_init() is the obvious place to do such initializations,
but arch_cpu_finalize_init() is invoked too late in start_kernel() e.g. for
initializing the FPU completely. fork_init() requires that the FPU is
initialized as the size of task_struct on X86 depends on the size of the
required FPU register buffer.
Fortunately none of the init calls between calibrate_delay() and
arch_cpu_finalize_init() is relevant for the functionality of
arch_cpu_finalize_init().
Invoke it right after calibrate_delay() where everything which is relevant
for arch_cpu_finalize_init() has been set up already.
No functional change intended.
Signed-off-by: Thomas Gleixner <tglx@linutronix.de>
Reviewed-by: Rick Edgecombe <rick.p.edgecombe@intel.com>
Link: https://lore.kernel.org/r/20230613224545.612182854@linutronix.de
Signed-off-by: Daniel Sneddon <daniel.sneddon@linux.intel.com>
Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
commit 7725acaa4f0c04fbefb0e0d342635b967bb7d414 upstream
check_bugs() has become a dumping ground for all sorts of activities to
finalize the CPU initialization before running the rest of the init code.
Most are empty, a few do actual bug checks, some do alternative patching
and some cobble a CPU advertisement string together....
Aside of that the current implementation requires duplicated function
declaration and mostly empty header files for them.
Provide a new function arch_cpu_finalize_init(). Provide a generic
declaration if CONFIG_ARCH_HAS_CPU_FINALIZE_INIT is selected and a stub
inline otherwise.
This requires a temporary #ifdef in start_kernel() which will be removed
along with check_bugs() once the architectures are converted over.
Signed-off-by: Thomas Gleixner <tglx@linutronix.de>
Link: https://lore.kernel.org/r/20230613224544.957805717@linutronix.de
Signed-off-by: Daniel Sneddon <daniel.sneddon@linux.intel.com>
Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
* Ignoring an ignore flag, yikes
* Also replace skip_initramf with want_initramf (omitting last letter for Magisk since it binary patches that out of kernel, I'm not even sure why we're supporting that mess)
Co-authored-by: Erfan Abdi <erfangplus@gmail.com>
Change-Id: Ifdf726f128bc66bf860bbb71024f94f56879710f
With PROBE_PREFER_ASYNCHRONOUS, drivers have ability to do asynchronous
probing, however this might break promise of ordering. This patch is to
add additional sync point between each init level.
Test: Boot
Bug: 63716230
Bug: 77146523
Bug: 115776306
Bug: 116061339
Change-Id: I2d2add41b29eaeecd6e68adcd09d9f5ec40fb97d
Signed-off-by: Wei Wang <wvw@google.com>
(cherry picked from commit 772b2385237f32140df38a51c644b3ad485a726e)
Signed-off-by: Panchajanya1999 <panchajanya@azure-dev.live>
atomic_t variables are currently used to implement reference
counters with the following properties:
- counter is initialized to 1 using atomic_set()
- a resource is freed upon counter reaching zero
- once counter reaches zero, its further
increments aren't allowed
- counter schema uses basic atomic operations
(set, inc, inc_not_zero, dec_and_test, etc.)
Such atomic variables should be converted to a newly provided
refcount_t type and API that prevents accidental counter overflows
and underflows. This is important since overflows and underflows
can lead to use-after-free situation and be exploitable.
The variable task_struct.usage is used as pure reference counter.
Convert it to refcount_t and fix up the operations.
** Important note for maintainers:
Some functions from refcount_t API defined in lib/refcount.c
have different memory ordering guarantees than their atomic
counterparts.
The full comparison can be seen in
https://lkml.org/lkml/2017/11/15/57 and it is hopefully soon
in state to be merged to the documentation tree.
Normally the differences should not matter since refcount_t provides
enough guarantees to satisfy the refcounting use cases, but in
some rare cases it might matter.
Please double check that you don't have some undocumented
memory guarantees for this variable usage.
For the task_struct.usage it might make a difference
in following places:
- put_task_struct(): decrement in refcount_dec_and_test() only
provides RELEASE ordering and control dependency on success
vs. fully ordered atomic counterpart
Suggested-by: Kees Cook <keescook@chromium.org>
Signed-off-by: Elena Reshetova <elena.reshetova@intel.com>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Reviewed-by: David Windsor <dwindsor@gmail.com>
Reviewed-by: Hans Liljestrand <ishkamiel@gmail.com>
Reviewed-by: Andrea Parri <andrea.parri@amarulasolutions.com>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Mike Galbraith <efault@gmx.de>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: akpm@linux-foundation.org
Cc: viro@zeniv.linux.org.uk
Link: https://lkml.kernel.org/r/1547814450-18902-5-git-send-email-elena.reshetova@intel.com
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Signed-off-by: Alexander Winkowski <dereference23@outlook.com>
Currently kmemleak uses a static early_log buffer to trace all memory
allocation/freeing before the slab allocator is initialised. Such early
log is replayed during kmemleak_init() to properly initialise the kmemleak
metadata for objects allocated up that point. With a memory pool that
does not rely on the slab allocator, it is possible to skip this early log
entirely.
In order to remove the early logging, consider kmemleak_enabled == 1 by
default while the kmem_cache availability is checked directly on the
object_cache and scan_area_cache variables. The RCU callback is only
invoked after object_cache has been initialised as we wouldn't have any
concurrent list traversal before this.
In order to reduce the number of callbacks before kmemleak is fully
initialised, move the kmemleak_init() call to mm_init().
[akpm@linux-foundation.org: coding-style fixes]
[akpm@linux-foundation.org: remove WARN_ON(), per Catalin]
Link: http://lkml.kernel.org/r/20190812160642.52134-4-catalin.marinas@arm.com
Signed-off-by: Catalin Marinas <catalin.marinas@arm.com>
Cc: Matthew Wilcox <willy@infradead.org>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Qian Cai <cai@lca.pw>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Andrzej Perczak <linux@andrzejperczak.com>
When SCHED_TUNE is disabled, certain elements in userspace, like
libperfmgr, may throw errors when it doesn't detect SCHEDTUNE-related nodes.
So, create a few dummy nodes to satisfy said userspace elements.
This is based on:
7725cb5bc1
With the following modifications:
- Completely remove CPUSET_ASSIST dependency
- Fix potential bootloop issues on some devices
- Place the Kconfig entry appropriately
- Improve code styling and readability
The cgroup CPU bandwidth controller allows to assign a specified
(maximum) bandwidth to the tasks of a group. However this bandwidth is
defined and enforced only on a temporal base, without considering the
actual frequency a CPU is running on. Thus, the amount of computation
completed by a task within an allocated bandwidth can be very different
depending on the actual frequency the CPU is running that task.
The amount of computation can be affected also by the specific CPU a
task is running on, especially when running on asymmetric capacity
systems like Arm's big.LITTLE.
With the availability of schedutil, the scheduler is now able
to drive frequency selections based on actual task utilization.
Moreover, the utilization clamping support provides a mechanism to
bias the frequency selection operated by schedutil depending on
constraints assigned to the tasks currently RUNNABLE on a CPU.
Giving the mechanisms described above, it is now possible to extend the
cpu controller to specify the minimum (or maximum) utilization which
should be considered for tasks RUNNABLE on a cpu.
This makes it possible to better defined the actual computational
power assigned to task groups, thus improving the cgroup CPU bandwidth
controller which is currently based just on time constraints.
Extend the CPU controller with a couple of new attributes uclamp.{min,max}
which allow to enforce utilization boosting and capping for all the
tasks in a group.
Specifically:
- uclamp.min: defines the minimum utilization which should be considered
i.e. the RUNNABLE tasks of this group will run at least at a
minimum frequency which corresponds to the uclamp.min
utilization
- uclamp.max: defines the maximum utilization which should be considered
i.e. the RUNNABLE tasks of this group will run up to a
maximum frequency which corresponds to the uclamp.max
utilization
These attributes:
a) are available only for non-root nodes, both on default and legacy
hierarchies, while system wide clamps are defined by a generic
interface which does not depends on cgroups. This system wide
interface enforces constraints on tasks in the root node.
b) enforce effective constraints at each level of the hierarchy which
are a restriction of the group requests considering its parent's
effective constraints. Root group effective constraints are defined
by the system wide interface.
This mechanism allows each (non-root) level of the hierarchy to:
- request whatever clamp values it would like to get
- effectively get only up to the maximum amount allowed by its parent
c) have higher priority than task-specific clamps, defined via
sched_setattr(), thus allowing to control and restrict task requests.
Add two new attributes to the cpu controller to collect "requested"
clamp values. Allow that at each non-root level of the hierarchy.
Keep it simple by not caring now about "effective" values computation
and propagation along the hierarchy.
Update sysctl_sched_uclamp_handler() to use the newly introduced
uclamp_mutex so that we serialize system default updates with cgroup
relate updates.
Bug: 120440300
Signed-off-by: Patrick Bellasi <patrick.bellasi@arm.com>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Reviewed-by: Michal Koutny <mkoutny@suse.com>
Acked-by: Tejun Heo <tj@kernel.org>
Cc: Alessio Balsini <balsini@android.com>
Cc: Dietmar Eggemann <dietmar.eggemann@arm.com>
Cc: Joel Fernandes <joelaf@google.com>
Cc: Juri Lelli <juri.lelli@redhat.com>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Morten Rasmussen <morten.rasmussen@arm.com>
Cc: Paul Turner <pjt@google.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Quentin Perret <quentin.perret@arm.com>
Cc: Rafael J . Wysocki <rafael.j.wysocki@intel.com>
Cc: Steve Muckle <smuckle@google.com>
Cc: Suren Baghdasaryan <surenb@google.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Todd Kjos <tkjos@google.com>
Cc: Vincent Guittot <vincent.guittot@linaro.org>
Cc: Viresh Kumar <viresh.kumar@linaro.org>
Link: https://lkml.kernel.org/r/20190822132811.31294-2-patrick.bellasi@arm.com
Signed-off-by: Ingo Molnar <mingo@kernel.org>
(cherry picked from commit 2480c093130f64ac3a410504fa8b3db1fc4b87ce)
Signed-off-by: Qais Yousef <qais.yousef@arm.com>
Change-Id: I0285c44910bf073b80d7996361e6698bc5aedfae
Signed-off-by: Quentin Perret <qperret@google.com>
Utilization clamping allows to clamp the CPU's utilization within a
[util_min, util_max] range, depending on the set of RUNNABLE tasks on
that CPU. Each task references two "clamp buckets" defining its minimum
and maximum (util_{min,max}) utilization "clamp values". A CPU's clamp
bucket is active if there is at least one RUNNABLE tasks enqueued on
that CPU and refcounting that bucket.
When a task is {en,de}queued {on,from} a rq, the set of active clamp
buckets on that CPU can change. If the set of active clamp buckets
changes for a CPU a new "aggregated" clamp value is computed for that
CPU. This is because each clamp bucket enforces a different utilization
clamp value.
Clamp values are always MAX aggregated for both util_min and util_max.
This ensures that no task can affect the performance of other
co-scheduled tasks which are more boosted (i.e. with higher util_min
clamp) or less capped (i.e. with higher util_max clamp).
A task has:
task_struct::uclamp[clamp_id]::bucket_id
to track the "bucket index" of the CPU's clamp bucket it refcounts while
enqueued, for each clamp index (clamp_id).
A runqueue has:
rq::uclamp[clamp_id]::bucket[bucket_id].tasks
to track how many RUNNABLE tasks on that CPU refcount each
clamp bucket (bucket_id) of a clamp index (clamp_id).
It also has a:
rq::uclamp[clamp_id]::bucket[bucket_id].value
to track the clamp value of each clamp bucket (bucket_id) of a clamp
index (clamp_id).
The rq::uclamp::bucket[clamp_id][] array is scanned every time it's
needed to find a new MAX aggregated clamp value for a clamp_id. This
operation is required only when it's dequeued the last task of a clamp
bucket tracking the current MAX aggregated clamp value. In this case,
the CPU is either entering IDLE or going to schedule a less boosted or
more clamped task.
The expected number of different clamp values configured at build time
is small enough to fit the full unordered array into a single cache
line, for configurations of up to 7 buckets.
Add to struct rq the basic data structures required to refcount the
number of RUNNABLE tasks for each clamp bucket. Add also the max
aggregation required to update the rq's clamp value at each
enqueue/dequeue event.
Use a simple linear mapping of clamp values into clamp buckets.
Pre-compute and cache bucket_id to avoid integer divisions at
enqueue/dequeue time.
Bug: 120440300
Signed-off-by: Patrick Bellasi <patrick.bellasi@arm.com>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Cc: Alessio Balsini <balsini@android.com>
Cc: Dietmar Eggemann <dietmar.eggemann@arm.com>
Cc: Joel Fernandes <joelaf@google.com>
Cc: Juri Lelli <juri.lelli@redhat.com>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Morten Rasmussen <morten.rasmussen@arm.com>
Cc: Paul Turner <pjt@google.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Quentin Perret <quentin.perret@arm.com>
Cc: Rafael J . Wysocki <rafael.j.wysocki@intel.com>
Cc: Steve Muckle <smuckle@google.com>
Cc: Suren Baghdasaryan <surenb@google.com>
Cc: Tejun Heo <tj@kernel.org>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Todd Kjos <tkjos@google.com>
Cc: Vincent Guittot <vincent.guittot@linaro.org>
Cc: Viresh Kumar <viresh.kumar@linaro.org>
Link: https://lkml.kernel.org/r/20190621084217.8167-2-patrick.bellasi@arm.com
Signed-off-by: Ingo Molnar <mingo@kernel.org>
(cherry picked from commit 69842cba9ace84849bb9b8edcdf2cefccd97901c)
Signed-off-by: Qais Yousef <qais.yousef@arm.com>
Change-Id: I2c2c23572fb82e004f815cc9c783881355df6836
Signed-off-by: Quentin Perret <qperret@google.com>
Architectures that are capable can select
HAVE_LD_DEAD_CODE_DATA_ELIMINATION to enable selection of that
option (as an EXPERT kernel option).
Signed-off-by: Nicholas Piggin <npiggin@gmail.com>
Signed-off-by: Masahiro Yamada <yamada.masahiro@socionext.com>
commit 2f14062bb14b0fcfcc21e6dc7d5b5c0d25966164 upstream.
Currently, start_kernel() adds latent entropy and the command line to
the entropy bool *after* the RNG has been initialized, deferring when
it's actually used by things like stack canaries until the next time
the pool is seeded. This surely is not intended.
Rather than splitting up which entropy gets added where and when between
start_kernel() and random_init(), just do everything in random_init(),
which should eliminate these kinds of bugs in the future.
While we're at it, rename the awkwardly titled "rand_initialize()" to
the more standard "random_init()" nomenclature.
Reviewed-by: Dominik Brodowski <linux@dominikbrodowski.net>
Signed-off-by: Jason A. Donenfeld <Jason@zx2c4.com>
Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
