Merge tag 'wq-for-6.6' of git://git.kernel.org/pub/scm/linux/kernel/git/tj/wq

Pull workqueue updates from Tejun Heo:

 - Unbound workqueues now support more flexible affinity scopes.

   The default behavior is to soft-affine according to last level cache
   boundaries. A work item queued from a given LLC is executed by a
   worker running on the same LLC but the worker may be moved across
   cache boundaries as the scheduler sees fit. On machines which
   multiple L3 caches, which are becoming more popular along with
   chiplet designs, this improves cache locality while not harming work
   conservation too much.

   Unbound workqueues are now also a lot more flexible in terms of
   execution affinity. Differeing levels of affinity scopes are
   supported and both the default and per-workqueue affinity settings
   can be modified dynamically. This should help working around amny of
   sub-optimal behaviors observed recently with asymmetric ARM CPUs.

   This involved signficant restructuring of workqueue code. Nothing was
   reported yet but there's some risk of subtle regressions. Should keep
   an eye out.

 - Rescuer workers now has more identifiable comms.

 - workqueue.unbound_cpus added so that CPUs which can be used by
   workqueue can be constrained early during boot.

 - Now that all the in-tree users have been flushed out, trigger warning
   if system-wide workqueues are flushed.

* tag 'wq-for-6.6' of git://git.kernel.org/pub/scm/linux/kernel/git/tj/wq: (31 commits)
  workqueue: fix data race with the pwq->stats[] increment
  workqueue: Rename rescuer kworker
  workqueue: Make default affinity_scope dynamically updatable
  workqueue: Add "Affinity Scopes and Performance" section to documentation
  workqueue: Implement non-strict affinity scope for unbound workqueues
  workqueue: Add workqueue_attrs->__pod_cpumask
  workqueue: Factor out need_more_worker() check and worker wake-up
  workqueue: Factor out work to worker assignment and collision handling
  workqueue: Add multiple affinity scopes and interface to select them
  workqueue: Modularize wq_pod_type initialization
  workqueue: Add tools/workqueue/wq_dump.py which prints out workqueue configuration
  workqueue: Generalize unbound CPU pods
  workqueue: Factor out clearing of workqueue-only attrs fields
  workqueue: Factor out actual cpumask calculation to reduce subtlety in wq_update_pod()
  workqueue: Initialize unbound CPU pods later in the boot
  workqueue: Move wq_pod_init() below workqueue_init()
  workqueue: Rename NUMA related names to use pod instead
  workqueue: Rename workqueue_attrs->no_numa to ->ordered
  workqueue: Make unbound workqueues to use per-cpu pool_workqueues
  workqueue: Call wq_update_unbound_numa() on all CPUs in NUMA node on CPU hotplug
  ...

1 files changed, 337 insertions, 19 deletions

diff --git a/Documentation/core-api/workqueue.rst b/Documentation/core-api/workqueue.rst
index a4c9b9d1905f..5d7b01aed1fe 100644
--- a/Documentation/core-api/workqueue.rst
+++ b/Documentation/core-api/workqueue.rst
@@ -1,6 +1,6 @@
-====================================
-Concurrency Managed Workqueue (cmwq)
-====================================
+=========
+Workqueue
+=========
 
 :Date: September, 2010
 :Author: Tejun Heo <tj@kernel.org>
@@ -25,8 +25,8 @@ there is no work item left on the workqueue the worker becomes idle.
 When a new work item gets queued, the worker begins executing again.
 
 
-Why cmwq?
-=========
+Why Concurrency Managed Workqueue?
+==================================
 
 In the original wq implementation, a multi threaded (MT) wq had one
 worker thread per CPU and a single threaded (ST) wq had one worker
@@ -220,17 +220,16 @@ resources, scheduled and executed.
 ``max_active``
 --------------
 
-``@max_active`` determines the maximum number of execution contexts
-per CPU which can be assigned to the work items of a wq.  For example,
-with ``@max_active`` of 16, at most 16 work items of the wq can be
-executing at the same time per CPU.
+``@max_active`` determines the maximum number of execution contexts per
+CPU which can be assigned to the work items of a wq. For example, with
+``@max_active`` of 16, at most 16 work items of the wq can be executing
+at the same time per CPU. This is always a per-CPU attribute, even for
+unbound workqueues.
 
-Currently, for a bound wq, the maximum limit for ``@max_active`` is
-512 and the default value used when 0 is specified is 256.  For an
-unbound wq, the limit is higher of 512 and 4 *
-``num_possible_cpus()``.  These values are chosen sufficiently high
-such that they are not the limiting factor while providing protection
-in runaway cases.
+The maximum limit for ``@max_active`` is 512 and the default value used
+when 0 is specified is 256. These values are chosen sufficiently high
+such that they are not the limiting factor while providing protection in
+runaway cases.
 
 The number of active work items of a wq is usually regulated by the
 users of the wq, more specifically, by how many work items the users
@@ -348,27 +347,346 @@ Guidelines
   level of locality in wq operations and work item execution.
 
 
+Affinity Scopes
+===============
+
+An unbound workqueue groups CPUs according to its affinity scope to improve
+cache locality. For example, if a workqueue is using the default affinity
+scope of "cache", it will group CPUs according to last level cache
+boundaries. A work item queued on the workqueue will be assigned to a worker
+on one of the CPUs which share the last level cache with the issuing CPU.
+Once started, the worker may or may not be allowed to move outside the scope
+depending on the ``affinity_strict`` setting of the scope.
+
+Workqueue currently supports the following affinity scopes.
+
+``default``
+  Use the scope in module parameter ``workqueue.default_affinity_scope``
+  which is always set to one of the scopes below.
+
+``cpu``
+  CPUs are not grouped. A work item issued on one CPU is processed by a
+  worker on the same CPU. This makes unbound workqueues behave as per-cpu
+  workqueues without concurrency management.
+
+``smt``
+  CPUs are grouped according to SMT boundaries. This usually means that the
+  logical threads of each physical CPU core are grouped together.
+
+``cache``
+  CPUs are grouped according to cache boundaries. Which specific cache
+  boundary is used is determined by the arch code. L3 is used in a lot of
+  cases. This is the default affinity scope.
+
+``numa``
+  CPUs are grouped according to NUMA bounaries.
+
+``system``
+  All CPUs are put in the same group. Workqueue makes no effort to process a
+  work item on a CPU close to the issuing CPU.
+
+The default affinity scope can be changed with the module parameter
+``workqueue.default_affinity_scope`` and a specific workqueue's affinity
+scope can be changed using ``apply_workqueue_attrs()``.
+
+If ``WQ_SYSFS`` is set, the workqueue will have the following affinity scope
+related interface files under its ``/sys/devices/virtual/WQ_NAME/``
+directory.
+
+``affinity_scope``
+  Read to see the current affinity scope. Write to change.
+
+  When default is the current scope, reading this file will also show the
+  current effective scope in parentheses, for example, ``default (cache)``.
+
+``affinity_strict``
+  0 by default indicating that affinity scopes are not strict. When a work
+  item starts execution, workqueue makes a best-effort attempt to ensure
+  that the worker is inside its affinity scope, which is called
+  repatriation. Once started, the scheduler is free to move the worker
+  anywhere in the system as it sees fit. This enables benefiting from scope
+  locality while still being able to utilize other CPUs if necessary and
+  available.
+
+  If set to 1, all workers of the scope are guaranteed always to be in the
+  scope. This may be useful when crossing affinity scopes has other
+  implications, for example, in terms of power consumption or workload
+  isolation. Strict NUMA scope can also be used to match the workqueue
+  behavior of older kernels.
+
+
+Affinity Scopes and Performance
+===============================
+
+It'd be ideal if an unbound workqueue's behavior is optimal for vast
+majority of use cases without further tuning. Unfortunately, in the current
+kernel, there exists a pronounced trade-off between locality and utilization
+necessitating explicit configurations when workqueues are heavily used.
+
+Higher locality leads to higher efficiency where more work is performed for
+the same number of consumed CPU cycles. However, higher locality may also
+cause lower overall system utilization if the work items are not spread
+enough across the affinity scopes by the issuers. The following performance
+testing with dm-crypt clearly illustrates this trade-off.
+
+The tests are run on a CPU with 12-cores/24-threads split across four L3
+caches (AMD Ryzen 9 3900x). CPU clock boost is turned off for consistency.
+``/dev/dm-0`` is a dm-crypt device created on NVME SSD (Samsung 990 PRO) and
+opened with ``cryptsetup`` with default settings.
+
+
+Scenario 1: Enough issuers and work spread across the machine
+-------------------------------------------------------------
+
+The command used: ::
+
+  $ fio --filename=/dev/dm-0 --direct=1 --rw=randrw --bs=32k --ioengine=libaio \
+    --iodepth=64 --runtime=60 --numjobs=24 --time_based --group_reporting \
+    --name=iops-test-job --verify=sha512
+
+There are 24 issuers, each issuing 64 IOs concurrently. ``--verify=sha512``
+makes ``fio`` generate and read back the content each time which makes
+execution locality matter between the issuer and ``kcryptd``. The followings
+are the read bandwidths and CPU utilizations depending on different affinity
+scope settings on ``kcryptd`` measured over five runs. Bandwidths are in
+MiBps, and CPU util in percents.
+
+.. list-table::
+   :widths: 16 20 20
+   :header-rows: 1
+
+   * - Affinity
+     - Bandwidth (MiBps)
+     - CPU util (%)
+
+   * - system
+     - 1159.40 ±1.34
+     - 99.31 ±0.02
+
+   * - cache
+     - 1166.40 ±0.89
+     - 99.34 ±0.01
+
+   * - cache (strict)
+     - 1166.00 ±0.71
+     - 99.35 ±0.01
+
+With enough issuers spread across the system, there is no downside to
+"cache", strict or otherwise. All three configurations saturate the whole
+machine but the cache-affine ones outperform by 0.6% thanks to improved
+locality.
+
+
+Scenario 2: Fewer issuers, enough work for saturation
+-----------------------------------------------------
+
+The command used: ::
+
+  $ fio --filename=/dev/dm-0 --direct=1 --rw=randrw --bs=32k \
+    --ioengine=libaio --iodepth=64 --runtime=60 --numjobs=8 \
+    --time_based --group_reporting --name=iops-test-job --verify=sha512
+
+The only difference from the previous scenario is ``--numjobs=8``. There are
+a third of the issuers but is still enough total work to saturate the
+system.
+
+.. list-table::
+   :widths: 16 20 20
+   :header-rows: 1
+
+   * - Affinity
+     - Bandwidth (MiBps)
+     - CPU util (%)
+
+   * - system
+     - 1155.40 ±0.89
+     - 97.41 ±0.05
+
+   * - cache
+     - 1154.40 ±1.14
+     - 96.15 ±0.09
+
+   * - cache (strict)
+     - 1112.00 ±4.64
+     - 93.26 ±0.35
+
+This is more than enough work to saturate the system. Both "system" and
+"cache" are nearly saturating the machine but not fully. "cache" is using
+less CPU but the better efficiency puts it at the same bandwidth as
+"system".
+
+Eight issuers moving around over four L3 cache scope still allow "cache
+(strict)" to mostly saturate the machine but the loss of work conservation
+is now starting to hurt with 3.7% bandwidth loss.
+
+
+Scenario 3: Even fewer issuers, not enough work to saturate
+-----------------------------------------------------------
+
+The command used: ::
+
+  $ fio --filename=/dev/dm-0 --direct=1 --rw=randrw --bs=32k \
+    --ioengine=libaio --iodepth=64 --runtime=60 --numjobs=4 \
+    --time_based --group_reporting --name=iops-test-job --verify=sha512
+
+Again, the only difference is ``--numjobs=4``. With the number of issuers
+reduced to four, there now isn't enough work to saturate the whole system
+and the bandwidth becomes dependent on completion latencies.
+
+.. list-table::
+   :widths: 16 20 20
+   :header-rows: 1
+
+   * - Affinity
+     - Bandwidth (MiBps)
+     - CPU util (%)
+
+   * - system
+     - 993.60 ±1.82
+     - 75.49 ±0.06
+
+   * - cache
+     - 973.40 ±1.52
+     - 74.90 ±0.07
+
+   * - cache (strict)
+     - 828.20 ±4.49
+     - 66.84 ±0.29
+
+Now, the tradeoff between locality and utilization is clearer. "cache" shows
+2% bandwidth loss compared to "system" and "cache (struct)" whopping 20%.
+
+
+Conclusion and Recommendations
+------------------------------
+
+In the above experiments, the efficiency advantage of the "cache" affinity
+scope over "system" is, while consistent and noticeable, small. However, the
+impact is dependent on the distances between the scopes and may be more
+pronounced in processors with more complex topologies.
+
+While the loss of work-conservation in certain scenarios hurts, it is a lot
+better than "cache (strict)" and maximizing workqueue utilization is
+unlikely to be the common case anyway. As such, "cache" is the default
+affinity scope for unbound pools.
+
+* As there is no one option which is great for most cases, workqueue usages
+  that may consume a significant amount of CPU are recommended to configure
+  the workqueues using ``apply_workqueue_attrs()`` and/or enable
+  ``WQ_SYSFS``.
+
+* An unbound workqueue with strict "cpu" affinity scope behaves the same as
+  ``WQ_CPU_INTENSIVE`` per-cpu workqueue. There is no real advanage to the
+  latter and an unbound workqueue provides a lot more flexibility.
+
+* Affinity scopes are introduced in Linux v6.5. To emulate the previous
+  behavior, use strict "numa" affinity scope.
+
+* The loss of work-conservation in non-strict affinity scopes is likely
+  originating from the scheduler. There is no theoretical reason why the
+  kernel wouldn't be able to do the right thing and maintain
+  work-conservation in most cases. As such, it is possible that future
+  scheduler improvements may make most of these tunables unnecessary.
+
+
+Examining Configuration
+=======================
+
+Use tools/workqueue/wq_dump.py to examine unbound CPU affinity
+configuration, worker pools and how workqueues map to the pools: ::
+
+  $ tools/workqueue/wq_dump.py
+  Affinity Scopes
+  ===============
+  wq_unbound_cpumask=0000000f
+
+  CPU
+    nr_pods  4
+    pod_cpus [0]=00000001 [1]=00000002 [2]=00000004 [3]=00000008
+    pod_node [0]=0 [1]=0 [2]=1 [3]=1
+    cpu_pod  [0]=0 [1]=1 [2]=2 [3]=3
+
+  SMT
+    nr_pods  4
+    pod_cpus [0]=00000001 [1]=00000002 [2]=00000004 [3]=00000008
+    pod_node [0]=0 [1]=0 [2]=1 [3]=1
+    cpu_pod  [0]=0 [1]=1 [2]=2 [3]=3
+
+  CACHE (default)
+    nr_pods  2
+    pod_cpus [0]=00000003 [1]=0000000c
+    pod_node [0]=0 [1]=1
+    cpu_pod  [0]=0 [1]=0 [2]=1 [3]=1
+
+  NUMA
+    nr_pods  2
+    pod_cpus [0]=00000003 [1]=0000000c
+    pod_node [0]=0 [1]=1
+    cpu_pod  [0]=0 [1]=0 [2]=1 [3]=1
+
+  SYSTEM
+    nr_pods  1
+    pod_cpus [0]=0000000f
+    pod_node [0]=-1
+    cpu_pod  [0]=0 [1]=0 [2]=0 [3]=0
+
+  Worker Pools
+  ============
+  pool[00] ref= 1 nice=  0 idle/workers=  4/  4 cpu=  0
+  pool[01] ref= 1 nice=-20 idle/workers=  2/  2 cpu=  0
+  pool[02] ref= 1 nice=  0 idle/workers=  4/  4 cpu=  1
+  pool[03] ref= 1 nice=-20 idle/workers=  2/  2 cpu=  1
+  pool[04] ref= 1 nice=  0 idle/workers=  4/  4 cpu=  2
+  pool[05] ref= 1 nice=-20 idle/workers=  2/  2 cpu=  2
+  pool[06] ref= 1 nice=  0 idle/workers=  3/  3 cpu=  3
+  pool[07] ref= 1 nice=-20 idle/workers=  2/  2 cpu=  3
+  pool[08] ref=42 nice=  0 idle/workers=  6/  6 cpus=0000000f
+  pool[09] ref=28 nice=  0 idle/workers=  3/  3 cpus=00000003
+  pool[10] ref=28 nice=  0 idle/workers= 17/ 17 cpus=0000000c
+  pool[11] ref= 1 nice=-20 idle/workers=  1/  1 cpus=0000000f
+  pool[12] ref= 2 nice=-20 idle/workers=  1/  1 cpus=00000003
+  pool[13] ref= 2 nice=-20 idle/workers=  1/  1 cpus=0000000c
+
+  Workqueue CPU -> pool
+  =====================
+  [    workqueue \ CPU              0  1  2  3 dfl]
+  events                   percpu   0  2  4  6
+  events_highpri           percpu   1  3  5  7
+  events_long              percpu   0  2  4  6
+  events_unbound           unbound  9  9 10 10  8
+  events_freezable         percpu   0  2  4  6
+  events_power_efficient   percpu   0  2  4  6
+  events_freezable_power_  percpu   0  2  4  6
+  rcu_gp                   percpu   0  2  4  6
+  rcu_par_gp               percpu   0  2  4  6
+  slub_flushwq             percpu   0  2  4  6
+  netns                    ordered  8  8  8  8  8
+  ...
+
+See the command's help message for more info.
+
+
 Monitoring
 ==========
 
 Use tools/workqueue/wq_monitor.py to monitor workqueue operations: ::
 
   $ tools/workqueue/wq_monitor.py events
-                              total  infl  CPUtime  CPUhog  CMwake  mayday rescued
+                              total  infl  CPUtime  CPUhog CMW/RPR  mayday rescued
   events                      18545     0      6.1       0       5       -       -
   events_highpri                  8     0      0.0       0       0       -       -
   events_long                     3     0      0.0       0       0       -       -
-  events_unbound              38306     0      0.1       -       -       -       -
+  events_unbound              38306     0      0.1       -       7       -       -
   events_freezable                0     0      0.0       0       0       -       -
   events_power_efficient      29598     0      0.2       0       0       -       -
   events_freezable_power_        10     0      0.0       0       0       -       -
   sock_diag_events                0     0      0.0       0       0       -       -
 
-                              total  infl  CPUtime  CPUhog  CMwake  mayday rescued
+                              total  infl  CPUtime  CPUhog CMW/RPR  mayday rescued
   events                      18548     0      6.1       0       5       -       -
   events_highpri                  8     0      0.0       0       0       -       -
   events_long                     3     0      0.0       0       0       -       -
-  events_unbound              38322     0      0.1       -       -       -       -
+  events_unbound              38322     0      0.1       -       7       -       -
   events_freezable                0     0      0.0       0       0       -       -
   events_power_efficient      29603     0      0.2       0       0       -       -
   events_freezable_power_        10     0      0.0       0       0       -       -