2023-08-07 15:57:25 -10:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2023-08-07 15:57:25 -10:00
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2010-09-10 16:51:36 +02:00
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2017-09-18 13:10:15 -07:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2010-09-10 16:51:36 +02:00
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2013-07-30 08:30:16 -04:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2012-07-13 22:16:45 -07:00
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2013-08-21 08:50:41 +08:00
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2012-07-13 22:16:45 -07:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2016-10-28 10:14:11 +02:00
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2013-08-21 08:50:41 +08:00
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2010-09-10 16:51:36 +02:00
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2013-08-21 08:50:41 +08:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2017-09-18 13:10:15 -07:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2017-09-18 13:10:15 -07:00
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2016-10-28 10:14:11 +02:00
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workqueue: Make unbound workqueues to use per-cpu pool_workqueues
A pwq (pool_workqueue) represents an association between a workqueue and a
worker_pool. When a work item is queued, the workqueue selects the pwq to
use, which in turn determines the pool, and queues the work item to the pool
through the pwq. pwq is also what implements the maximum concurrency limit -
@max_active.
As a per-cpu workqueue should be assocaited with a different worker_pool on
each CPU, it always had per-cpu pwq's that are accessed through wq->cpu_pwq.
However, unbound workqueues were sharing a pwq within each NUMA node by
default. The sharing has several downsides:
* Because @max_active is per-pwq, the meaning of @max_active changes
depending on the machine configuration and whether workqueue NUMA locality
support is enabled.
* Makes per-cpu and unbound code deviate.
* Gets in the way of making workqueue CPU locality awareness more flexible.
This patch makes unbound workqueues use per-cpu pwq's the same way per-cpu
workqueues do by making the following changes:
* wq->numa_pwq_tbl[] is removed and unbound workqueues now use wq->cpu_pwq
just like per-cpu workqueues. wq->cpu_pwq is now RCU protected for unbound
workqueues.
* numa_pwq_tbl_install() is renamed to install_unbound_pwq() and installs
the specified pwq to the target CPU's wq->cpu_pwq.
* apply_wqattrs_prepare() now always allocates a separate pwq for each CPU
unless the workqueue is ordered. If ordered, all CPUs use wq->dfl_pwq.
This makes the return value of wq_calc_node_cpumask() unnecessary. It now
returns void.
* @max_active now means the same thing for both per-cpu and unbound
workqueues. WQ_UNBOUND_MAX_ACTIVE now equals WQ_MAX_ACTIVE and
documentation is updated accordingly. WQ_UNBOUND_MAX_ACTIVE is no longer
used in workqueue implementation and will be removed later.
* All unbound pwq operations which used to be per-numa-node are now per-cpu.
For most unbound workqueue users, this shouldn't cause noticeable changes.
Work item issue and completion will be a small bit faster, flush_workqueue()
would become a bit more expensive, and the total concurrency limit would
likely become higher. All @max_active==1 use cases are currently being
audited for conversion into alloc_ordered_workqueue() and they shouldn't be
affected once the audit and conversion is complete.
One area where the behavior change may be more noticeable is
workqueue_congested() as the reported congestion state is now per CPU
instead of NUMA node. There are only two users of this interface -
drivers/infiniband/hw/hfi1 and net/smc. Maintainers of both subsystems are
cc'd. Inputs on the behavior change would be very much appreciated.
Signed-off-by: Tejun Heo <tj@kernel.org>
Acked-by: Dennis Dalessandro <dennis.dalessandro@cornelisnetworks.com>
Cc: Jason Gunthorpe <jgg@ziepe.ca>
Cc: Leon Romanovsky <leon@kernel.org>
Cc: Karsten Graul <kgraul@linux.ibm.com>
Cc: Wenjia Zhang <wenjia@linux.ibm.com>
Cc: Jan Karcher <jaka@linux.ibm.com>
2023-08-07 15:57:23 -10:00
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2010-09-10 16:51:36 +02:00
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2017-07-18 11:12:53 -07:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2017-07-18 11:12:53 -07:00
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2023-10-12 15:17:38 +08:00
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2017-09-18 13:10:15 -07:00
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2017-07-18 11:12:53 -07:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2010-10-11 15:12:27 +02:00
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2016-10-28 10:14:11 +02:00
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2010-09-10 16:51:36 +02:00
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2011-03-31 13:40:42 +02:00
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2023-08-07 15:57:24 -10:00
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workqueue: Implement non-strict affinity scope for unbound workqueues
An unbound workqueue can be served by multiple worker_pools to improve
locality. The segmentation is achieved by grouping CPUs into pods. By
default, the cache boundaries according to cpus_share_cache() define the
CPUs are grouped. Let's a workqueue is allowed to run on all CPUs and the
system has two L3 caches. The workqueue would be mapped to two worker_pools
each serving one L3 cache domains.
While this improves locality, because the pod boundaries are strict, it
limits the total bandwidth a given issuer can consume. For example, let's
say there is a thread pinned to a CPU issuing enough work items to saturate
the whole machine. With the machine segmented into two pods, no matter how
many work items it issues, it can only use half of the CPUs on the system.
While this limitation has existed for a very long time, it wasn't very
pronounced because the affinity grouping used to be always by NUMA nodes.
With cache boundaries as the default and support for even finer grained
scopes (smt and cpu), it is now an a lot more pressing problem.
This patch implements non-strict affinity scope where the pod boundaries
aren't enforced strictly. Going back to the previous example, the workqueue
would still be mapped to two worker_pools; however, the affinity enforcement
would be soft. The workers in both pools would have their cpus_allowed set
to the whole machine thus allowing the scheduler to migrate them anywhere on
the machine. However, whenever an idle worker is woken up, the workqueue
code asks the scheduler to bring back the task within the pod if the worker
is outside. ie. work items start executing within its affinity scope but can
be migrated outside as the scheduler sees fit. This removes the hard cap on
utilization while maintaining the benefits of affinity scopes.
After the earlier ->__pod_cpumask changes, the implementation is pretty
simple. When non-strict which is the new default:
* pool_allowed_cpus() returns @pool->attrs->cpumask instead of
->__pod_cpumask so that the workers are allowed to run on any CPU that
the associated workqueues allow.
* If the idle worker task's ->wake_cpu is outside the pod, kick_pool() sets
the field to a CPU within the pod.
This would be the first use of task_struct->wake_cpu outside scheduler
proper, so it isn't clear whether this would be acceptable. However, other
methods of migrating tasks are significantly more expensive and are likely
prohibitively so if we want to do this on every work item. This needs
discussion with scheduler folks.
There is also a race window where setting ->wake_cpu wouldn't be effective
as the target task is still on CPU. However, the window is pretty small and
this being a best-effort optimization, it doesn't seem to warrant more
complexity at the moment.
While the non-strict cache affinity scopes seem to be the best option, the
performance picture interacts with the affinity scope and is a bit
complicated to fully discuss in this patch, so the behavior is made easily
selectable through wqattrs and sysfs and the next patch will add
documentation to discuss performance implications.
v2: pool->attrs->affn_strict is set to true for per-cpu worker_pools.
Signed-off-by: Tejun Heo <tj@kernel.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
2023-08-07 15:57:25 -10:00
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2023-08-07 15:57:24 -10:00
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2023-08-07 15:57:25 -10:00
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2023-08-07 15:57:24 -10:00
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2023-10-12 15:17:38 +08:00
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2023-08-07 15:57:24 -10:00
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2023-08-07 15:57:25 -10:00
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workqueue: Implement non-strict affinity scope for unbound workqueues
An unbound workqueue can be served by multiple worker_pools to improve
locality. The segmentation is achieved by grouping CPUs into pods. By
default, the cache boundaries according to cpus_share_cache() define the
CPUs are grouped. Let's a workqueue is allowed to run on all CPUs and the
system has two L3 caches. The workqueue would be mapped to two worker_pools
each serving one L3 cache domains.
While this improves locality, because the pod boundaries are strict, it
limits the total bandwidth a given issuer can consume. For example, let's
say there is a thread pinned to a CPU issuing enough work items to saturate
the whole machine. With the machine segmented into two pods, no matter how
many work items it issues, it can only use half of the CPUs on the system.
While this limitation has existed for a very long time, it wasn't very
pronounced because the affinity grouping used to be always by NUMA nodes.
With cache boundaries as the default and support for even finer grained
scopes (smt and cpu), it is now an a lot more pressing problem.
This patch implements non-strict affinity scope where the pod boundaries
aren't enforced strictly. Going back to the previous example, the workqueue
would still be mapped to two worker_pools; however, the affinity enforcement
would be soft. The workers in both pools would have their cpus_allowed set
to the whole machine thus allowing the scheduler to migrate them anywhere on
the machine. However, whenever an idle worker is woken up, the workqueue
code asks the scheduler to bring back the task within the pod if the worker
is outside. ie. work items start executing within its affinity scope but can
be migrated outside as the scheduler sees fit. This removes the hard cap on
utilization while maintaining the benefits of affinity scopes.
After the earlier ->__pod_cpumask changes, the implementation is pretty
simple. When non-strict which is the new default:
* pool_allowed_cpus() returns @pool->attrs->cpumask instead of
->__pod_cpumask so that the workers are allowed to run on any CPU that
the associated workqueues allow.
* If the idle worker task's ->wake_cpu is outside the pod, kick_pool() sets
the field to a CPU within the pod.
This would be the first use of task_struct->wake_cpu outside scheduler
proper, so it isn't clear whether this would be acceptable. However, other
methods of migrating tasks are significantly more expensive and are likely
prohibitively so if we want to do this on every work item. This needs
discussion with scheduler folks.
There is also a race window where setting ->wake_cpu wouldn't be effective
as the target task is still on CPU. However, the window is pretty small and
this being a best-effort optimization, it doesn't seem to warrant more
complexity at the moment.
While the non-strict cache affinity scopes seem to be the best option, the
performance picture interacts with the affinity scope and is a bit
complicated to fully discuss in this patch, so the behavior is made easily
selectable through wqattrs and sysfs and the next patch will add
documentation to discuss performance implications.
v2: pool->attrs->affn_strict is set to true for per-cpu worker_pools.
Signed-off-by: Tejun Heo <tj@kernel.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
2023-08-07 15:57:25 -10:00
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2023-08-07 15:57:24 -10:00
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2023-08-07 15:57:25 -10:00
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2023-08-07 15:57:24 -10:00
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2023-08-07 15:57:24 -10:00
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2023-08-07 15:57:24 -10:00
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2023-05-17 17:02:08 -10:00
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workqueue: Implement non-strict affinity scope for unbound workqueues
An unbound workqueue can be served by multiple worker_pools to improve
locality. The segmentation is achieved by grouping CPUs into pods. By
default, the cache boundaries according to cpus_share_cache() define the
CPUs are grouped. Let's a workqueue is allowed to run on all CPUs and the
system has two L3 caches. The workqueue would be mapped to two worker_pools
each serving one L3 cache domains.
While this improves locality, because the pod boundaries are strict, it
limits the total bandwidth a given issuer can consume. For example, let's
say there is a thread pinned to a CPU issuing enough work items to saturate
the whole machine. With the machine segmented into two pods, no matter how
many work items it issues, it can only use half of the CPUs on the system.
While this limitation has existed for a very long time, it wasn't very
pronounced because the affinity grouping used to be always by NUMA nodes.
With cache boundaries as the default and support for even finer grained
scopes (smt and cpu), it is now an a lot more pressing problem.
This patch implements non-strict affinity scope where the pod boundaries
aren't enforced strictly. Going back to the previous example, the workqueue
would still be mapped to two worker_pools; however, the affinity enforcement
would be soft. The workers in both pools would have their cpus_allowed set
to the whole machine thus allowing the scheduler to migrate them anywhere on
the machine. However, whenever an idle worker is woken up, the workqueue
code asks the scheduler to bring back the task within the pod if the worker
is outside. ie. work items start executing within its affinity scope but can
be migrated outside as the scheduler sees fit. This removes the hard cap on
utilization while maintaining the benefits of affinity scopes.
After the earlier ->__pod_cpumask changes, the implementation is pretty
simple. When non-strict which is the new default:
* pool_allowed_cpus() returns @pool->attrs->cpumask instead of
->__pod_cpumask so that the workers are allowed to run on any CPU that
the associated workqueues allow.
* If the idle worker task's ->wake_cpu is outside the pod, kick_pool() sets
the field to a CPU within the pod.
This would be the first use of task_struct->wake_cpu outside scheduler
proper, so it isn't clear whether this would be acceptable. However, other
methods of migrating tasks are significantly more expensive and are likely
prohibitively so if we want to do this on every work item. This needs
discussion with scheduler folks.
There is also a race window where setting ->wake_cpu wouldn't be effective
as the target task is still on CPU. However, the window is pretty small and
this being a best-effort optimization, it doesn't seem to warrant more
complexity at the moment.
While the non-strict cache affinity scopes seem to be the best option, the
performance picture interacts with the affinity scope and is a bit
complicated to fully discuss in this patch, so the behavior is made easily
selectable through wqattrs and sysfs and the next patch will add
documentation to discuss performance implications.
v2: pool->attrs->affn_strict is set to true for per-cpu worker_pools.
Signed-off-by: Tejun Heo <tj@kernel.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
2023-08-07 15:57:25 -10:00
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|
2023-05-17 17:02:09 -10:00
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|
workqueue: Implement non-strict affinity scope for unbound workqueues
An unbound workqueue can be served by multiple worker_pools to improve
locality. The segmentation is achieved by grouping CPUs into pods. By
default, the cache boundaries according to cpus_share_cache() define the
CPUs are grouped. Let's a workqueue is allowed to run on all CPUs and the
system has two L3 caches. The workqueue would be mapped to two worker_pools
each serving one L3 cache domains.
While this improves locality, because the pod boundaries are strict, it
limits the total bandwidth a given issuer can consume. For example, let's
say there is a thread pinned to a CPU issuing enough work items to saturate
the whole machine. With the machine segmented into two pods, no matter how
many work items it issues, it can only use half of the CPUs on the system.
While this limitation has existed for a very long time, it wasn't very
pronounced because the affinity grouping used to be always by NUMA nodes.
With cache boundaries as the default and support for even finer grained
scopes (smt and cpu), it is now an a lot more pressing problem.
This patch implements non-strict affinity scope where the pod boundaries
aren't enforced strictly. Going back to the previous example, the workqueue
would still be mapped to two worker_pools; however, the affinity enforcement
would be soft. The workers in both pools would have their cpus_allowed set
to the whole machine thus allowing the scheduler to migrate them anywhere on
the machine. However, whenever an idle worker is woken up, the workqueue
code asks the scheduler to bring back the task within the pod if the worker
is outside. ie. work items start executing within its affinity scope but can
be migrated outside as the scheduler sees fit. This removes the hard cap on
utilization while maintaining the benefits of affinity scopes.
After the earlier ->__pod_cpumask changes, the implementation is pretty
simple. When non-strict which is the new default:
* pool_allowed_cpus() returns @pool->attrs->cpumask instead of
->__pod_cpumask so that the workers are allowed to run on any CPU that
the associated workqueues allow.
* If the idle worker task's ->wake_cpu is outside the pod, kick_pool() sets
the field to a CPU within the pod.
This would be the first use of task_struct->wake_cpu outside scheduler
proper, so it isn't clear whether this would be acceptable. However, other
methods of migrating tasks are significantly more expensive and are likely
prohibitively so if we want to do this on every work item. This needs
discussion with scheduler folks.
There is also a race window where setting ->wake_cpu wouldn't be effective
as the target task is still on CPU. However, the window is pretty small and
this being a best-effort optimization, it doesn't seem to warrant more
complexity at the moment.
While the non-strict cache affinity scopes seem to be the best option, the
performance picture interacts with the affinity scope and is a bit
complicated to fully discuss in this patch, so the behavior is made easily
selectable through wqattrs and sysfs and the next patch will add
documentation to discuss performance implications.
v2: pool->attrs->affn_strict is set to true for per-cpu worker_pools.
Signed-off-by: Tejun Heo <tj@kernel.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
2023-08-07 15:57:25 -10:00
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2023-05-17 17:02:09 -10:00
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workqueue: Implement non-strict affinity scope for unbound workqueues
An unbound workqueue can be served by multiple worker_pools to improve
locality. The segmentation is achieved by grouping CPUs into pods. By
default, the cache boundaries according to cpus_share_cache() define the
CPUs are grouped. Let's a workqueue is allowed to run on all CPUs and the
system has two L3 caches. The workqueue would be mapped to two worker_pools
each serving one L3 cache domains.
While this improves locality, because the pod boundaries are strict, it
limits the total bandwidth a given issuer can consume. For example, let's
say there is a thread pinned to a CPU issuing enough work items to saturate
the whole machine. With the machine segmented into two pods, no matter how
many work items it issues, it can only use half of the CPUs on the system.
While this limitation has existed for a very long time, it wasn't very
pronounced because the affinity grouping used to be always by NUMA nodes.
With cache boundaries as the default and support for even finer grained
scopes (smt and cpu), it is now an a lot more pressing problem.
This patch implements non-strict affinity scope where the pod boundaries
aren't enforced strictly. Going back to the previous example, the workqueue
would still be mapped to two worker_pools; however, the affinity enforcement
would be soft. The workers in both pools would have their cpus_allowed set
to the whole machine thus allowing the scheduler to migrate them anywhere on
the machine. However, whenever an idle worker is woken up, the workqueue
code asks the scheduler to bring back the task within the pod if the worker
is outside. ie. work items start executing within its affinity scope but can
be migrated outside as the scheduler sees fit. This removes the hard cap on
utilization while maintaining the benefits of affinity scopes.
After the earlier ->__pod_cpumask changes, the implementation is pretty
simple. When non-strict which is the new default:
* pool_allowed_cpus() returns @pool->attrs->cpumask instead of
->__pod_cpumask so that the workers are allowed to run on any CPU that
the associated workqueues allow.
* If the idle worker task's ->wake_cpu is outside the pod, kick_pool() sets
the field to a CPU within the pod.
This would be the first use of task_struct->wake_cpu outside scheduler
proper, so it isn't clear whether this would be acceptable. However, other
methods of migrating tasks are significantly more expensive and are likely
prohibitively so if we want to do this on every work item. This needs
discussion with scheduler folks.
There is also a race window where setting ->wake_cpu wouldn't be effective
as the target task is still on CPU. However, the window is pretty small and
this being a best-effort optimization, it doesn't seem to warrant more
complexity at the moment.
While the non-strict cache affinity scopes seem to be the best option, the
performance picture interacts with the affinity scope and is a bit
complicated to fully discuss in this patch, so the behavior is made easily
selectable through wqattrs and sysfs and the next patch will add
documentation to discuss performance implications.
v2: pool->attrs->affn_strict is set to true for per-cpu worker_pools.
Signed-off-by: Tejun Heo <tj@kernel.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
2023-08-07 15:57:25 -10:00
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2023-05-17 17:02:09 -10:00
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workqueue: Implement non-strict affinity scope for unbound workqueues
An unbound workqueue can be served by multiple worker_pools to improve
locality. The segmentation is achieved by grouping CPUs into pods. By
default, the cache boundaries according to cpus_share_cache() define the
CPUs are grouped. Let's a workqueue is allowed to run on all CPUs and the
system has two L3 caches. The workqueue would be mapped to two worker_pools
each serving one L3 cache domains.
While this improves locality, because the pod boundaries are strict, it
limits the total bandwidth a given issuer can consume. For example, let's
say there is a thread pinned to a CPU issuing enough work items to saturate
the whole machine. With the machine segmented into two pods, no matter how
many work items it issues, it can only use half of the CPUs on the system.
While this limitation has existed for a very long time, it wasn't very
pronounced because the affinity grouping used to be always by NUMA nodes.
With cache boundaries as the default and support for even finer grained
scopes (smt and cpu), it is now an a lot more pressing problem.
This patch implements non-strict affinity scope where the pod boundaries
aren't enforced strictly. Going back to the previous example, the workqueue
would still be mapped to two worker_pools; however, the affinity enforcement
would be soft. The workers in both pools would have their cpus_allowed set
to the whole machine thus allowing the scheduler to migrate them anywhere on
the machine. However, whenever an idle worker is woken up, the workqueue
code asks the scheduler to bring back the task within the pod if the worker
is outside. ie. work items start executing within its affinity scope but can
be migrated outside as the scheduler sees fit. This removes the hard cap on
utilization while maintaining the benefits of affinity scopes.
After the earlier ->__pod_cpumask changes, the implementation is pretty
simple. When non-strict which is the new default:
* pool_allowed_cpus() returns @pool->attrs->cpumask instead of
->__pod_cpumask so that the workers are allowed to run on any CPU that
the associated workqueues allow.
* If the idle worker task's ->wake_cpu is outside the pod, kick_pool() sets
the field to a CPU within the pod.
This would be the first use of task_struct->wake_cpu outside scheduler
proper, so it isn't clear whether this would be acceptable. However, other
methods of migrating tasks are significantly more expensive and are likely
prohibitively so if we want to do this on every work item. This needs
discussion with scheduler folks.
There is also a race window where setting ->wake_cpu wouldn't be effective
as the target task is still on CPU. However, the window is pretty small and
this being a best-effort optimization, it doesn't seem to warrant more
complexity at the moment.
While the non-strict cache affinity scopes seem to be the best option, the
performance picture interacts with the affinity scope and is a bit
complicated to fully discuss in this patch, so the behavior is made easily
selectable through wqattrs and sysfs and the next patch will add
documentation to discuss performance implications.
v2: pool->attrs->affn_strict is set to true for per-cpu worker_pools.
Signed-off-by: Tejun Heo <tj@kernel.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
2023-08-07 15:57:25 -10:00
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2023-05-17 17:02:09 -10:00
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2023-05-17 17:02:08 -10:00
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2016-10-28 10:14:11 +02:00
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2011-03-31 13:40:42 +02:00
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2016-10-28 10:14:11 +02:00
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2011-03-31 13:40:42 +02:00
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2016-10-28 10:14:11 +02:00
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2011-03-31 13:40:42 +02:00
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2015-05-05 12:49:00 +01:00
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2011-03-31 13:40:42 +02:00
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2016-10-28 10:14:11 +02:00
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2011-03-31 13:40:42 +02:00
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2023-01-25 14:32:51 -07:00
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2011-03-31 13:40:42 +02:00
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2016-10-28 10:14:11 +02:00
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2011-03-31 13:40:42 +02:00
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2016-10-28 10:14:11 +02:00
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2023-05-17 17:02:08 -10:00
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2021-10-22 08:42:08 +08:00
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2016-10-28 10:14:11 +02:00
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2020-09-28 16:49:26 +02:00
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