user/sven/linux.git/include/linux/workqueue.h, branch v6.7.6

workqueue: Provide one lock class key per work_on_cpu() callsite

2023-10-18T09:49:19Z

All callers of work_on_cpu() share the same lock class key for all the functions queued. As a result the workqueue related locking scenario for a function A may be spuriously accounted as an inversion against the locking scenario of function B such as in the following model: long A(void *arg) { mutex_lock(&mutex); mutex_unlock(&mutex); } long B(void *arg) { } void launchA(void) { work_on_cpu(0, A, NULL); } void launchB(void) { mutex_lock(&mutex); work_on_cpu(1, B, NULL); mutex_unlock(&mutex); } launchA and launchB running concurrently have no chance to deadlock. However the above can be reported by lockdep as a possible locking inversion because the works containing A() and B() are treated as belonging to the same locking class. The following shows an existing example of such a spurious lockdep splat: ====================================================== WARNING: possible circular locking dependency detected 6.6.0-rc1-00065-g934ebd6e5359 #35409 Not tainted ------------------------------------------------------ kworker/0:1/9 is trying to acquire lock: ffffffff9bc72f30 (cpu_hotplug_lock){++++}-{0:0}, at: _cpu_down+0x57/0x2b0 but task is already holding lock: ffff9e3bc0057e60 ((work_completion)(&wfc.work)){+.+.}-{0:0}, at: process_scheduled_works+0x216/0x500 which lock already depends on the new lock. the existing dependency chain (in reverse order) is: -> #2 ((work_completion)(&wfc.work)){+.+.}-{0:0}: __flush_work+0x83/0x4e0 work_on_cpu+0x97/0xc0 rcu_nocb_cpu_offload+0x62/0xb0 rcu_nocb_toggle+0xd0/0x1d0 kthread+0xe6/0x120 ret_from_fork+0x2f/0x40 ret_from_fork_asm+0x1b/0x30 -> #1 (rcu_state.barrier_mutex){+.+.}-{3:3}: __mutex_lock+0x81/0xc80 rcu_nocb_cpu_deoffload+0x38/0xb0 rcu_nocb_toggle+0x144/0x1d0 kthread+0xe6/0x120 ret_from_fork+0x2f/0x40 ret_from_fork_asm+0x1b/0x30 -> #0 (cpu_hotplug_lock){++++}-{0:0}: __lock_acquire+0x1538/0x2500 lock_acquire+0xbf/0x2a0 percpu_down_write+0x31/0x200 _cpu_down+0x57/0x2b0 __cpu_down_maps_locked+0x10/0x20 work_for_cpu_fn+0x15/0x20 process_scheduled_works+0x2a7/0x500 worker_thread+0x173/0x330 kthread+0xe6/0x120 ret_from_fork+0x2f/0x40 ret_from_fork_asm+0x1b/0x30 other info that might help us debug this: Chain exists of: cpu_hotplug_lock --> rcu_state.barrier_mutex --> (work_completion)(&wfc.work) Possible unsafe locking scenario: CPU0 CPU1 ---- ---- lock((work_completion)(&wfc.work)); lock(rcu_state.barrier_mutex); lock((work_completion)(&wfc.work)); lock(cpu_hotplug_lock); *** DEADLOCK *** 2 locks held by kworker/0:1/9: #0: ffff900481068b38 ((wq_completion)events){+.+.}-{0:0}, at: process_scheduled_works+0x212/0x500 #1: ffff9e3bc0057e60 ((work_completion)(&wfc.work)){+.+.}-{0:0}, at: process_scheduled_works+0x216/0x500 stack backtrace: CPU: 0 PID: 9 Comm: kworker/0:1 Not tainted 6.6.0-rc1-00065-g934ebd6e5359 #35409 Hardware name: QEMU Standard PC (Q35 + ICH9, 2009), BIOS rel-1.12.0-59-gc9ba5276e321-prebuilt.qemu.org 04/01/2014 Workqueue: events work_for_cpu_fn Call Trace: rcu-torture: rcu_torture_read_exit: Start of episode dump_stack_lvl+0x4a/0x80 check_noncircular+0x132/0x150 __lock_acquire+0x1538/0x2500 lock_acquire+0xbf/0x2a0 ? _cpu_down+0x57/0x2b0 percpu_down_write+0x31/0x200 ? _cpu_down+0x57/0x2b0 _cpu_down+0x57/0x2b0 __cpu_down_maps_locked+0x10/0x20 work_for_cpu_fn+0x15/0x20 process_scheduled_works+0x2a7/0x500 worker_thread+0x173/0x330 ? __pfx_worker_thread+0x10/0x10 kthread+0xe6/0x120 ? __pfx_kthread+0x10/0x10 ret_from_fork+0x2f/0x40 ? __pfx_kthread+0x10/0x10 ret_from_fork_asm+0x1b/0x30 Signed-off-by: Frederic Weisbecker Signed-off-by: Tejun Heo

workqueue: Make default affinity_scope dynamically updatable

2023-08-08T01:57:25Z

While workqueue.default_affinity_scope is writable, it only affects workqueues which are created afterwards and isn't very useful. Instead, let's introduce explicit "default" scope and update the effective scope dynamically when workqueue.default_affinity_scope is changed. Signed-off-by: Tejun Heo

workqueue: Implement non-strict affinity scope for unbound workqueues

2023-08-08T01:57:25Z

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 Cc: Peter Zijlstra Cc: Linus Torvalds

workqueue: Add workqueue_attrs->__pod_cpumask

2023-08-08T01:57:25Z

workqueue_attrs has two uses: * to specify the required unouned workqueue properties by users * to match worker_pool's properties to workqueues by core code For example, if the user wants to restrict a workqueue to run only CPUs 0 and 2, and the two CPUs are on different affinity scopes, the workqueue's attrs->cpumask would contains CPUs 0 and 2, and the workqueue would be associated with two worker_pools, one with attrs->cpumask containing just CPU 0 and the other CPU 2. Workqueue wants to support non-strict affinity scopes where work items are started in their matching affinity scopes but the scheduler is free to migrate them outside the starting scopes, which can enable utilizing the whole machine while maintaining most of the locality benefits from affinity scopes. To enable that, worker_pools need to distinguish the strict affinity that it has to follow (because that's the restriction coming from the user) and the soft affinity that it wants to apply when dispatching work items. Note that two worker_pools with different soft dispatching requirements have to be separate; otherwise, for example, we'd be ping-ponging worker threads across NUMA boundaries constantly. This patch adds workqueue_attrs->__pod_cpumask. The new field is double underscored as it's only used internally to distinguish worker_pools. A worker_pool's ->cpumask is now always the same as the online subset of allowed CPUs of the associated workqueues, and ->__pod_cpumask is the pod's subset of that ->cpumask. Going back to the example above, both worker_pools would have ->cpumask containing both CPUs 0 and 2 but one's ->__pod_cpumask would contain 0 while the other's 2. * pool_allowed_cpus() is added. It returns the worker_pool's strict cpumask that the pool's workers must stay within. This is currently always ->__pod_cpumask as all boundaries are still strict. * As a workqueue_attrs can now track both the associated workqueues' cpumask and its per-pod subset, wq_calc_pod_cpumask() no longer needs an external out-argument. Drop @cpumask and instead store the result in ->__pod_cpumask. * The above also simplifies apply_wqattrs_prepare() as the same workqueue_attrs can be used to create all pods associated with a workqueue. tmp_attrs is dropped. * wq_update_pod() is updated to use wqattrs_equal() to test whether a pwq update is needed instead of only comparing ->cpumask so that ->__pod_cpumask is compared too. It can directly compare ->__pod_cpumaks but the code is easier to understand and more robust this way. The only user-visible behavior change is that two workqueues with different cpumasks no longer can share worker_pools even when their pod subsets coincide. Going back to the example, let's say there's another workqueue with cpumask 0, 2, 3, where 2 and 3 are in the same pod. It would be mapped to two worker_pools - one with CPU 0, the other with 2 and 3. The former has the same cpumask as the first pod of the earlier example and would have shared the same worker_pool but that's no longer the case after this patch. The worker_pools would have the same ->__pod_cpumask but their ->cpumask's wouldn't match. While this is necessary to support non-strict affinity scopes, there can be further optimizations to maintain sharing among strict affinity scopes. However, non-strict affinity scopes are going to be preferable for most use cases and we don't see very diverse mixture of unbound workqueue cpumasks anyway, so the additional overhead doesn't seem to justify the extra complexity. v2: - wq_update_pod() was incorrectly comparing target_attrs->__pod_cpumask to pool->attrs->cpumask instead of its ->__pod_cpumask. Fix it by using wqattrs_equal() for comparison instead. - Per-cpu worker pools weren't initializing ->__pod_cpumask which caused a subtle problem later on. Set it to cpumask_of(cpu) like ->cpumask. Signed-off-by: Tejun Heo

workqueue: Add multiple affinity scopes and interface to select them

2023-08-08T01:57:24Z

Add three more affinity scopes - WQ_AFFN_CPU, SMT and CACHE - and make CACHE the default. The code changes to actually add the additional scopes are trivial. Also add module parameter "workqueue.default_affinity_scope" to override the default scope and "affinity_scope" sysfs file to configure it per workqueue. wq_dump.py and documentations are updated accordingly. This enables significant flexibility in configuring how unbound workqueues behave. If affinity scope is set to "cpu", it'll behave close to a per-cpu workqueue. On the other hand, "system" removes all locality boundaries. Many modern machines have multiple L3 caches often while being mostly uniform in terms of memory access. Thus, workqueue's previous behavior of spreading work items in each NUMA node had negative performance implications from unncessarily crossing L3 boundaries between issue and execution. However, picking a finer grained affinity scope also has a downside in that an issuer in one group can't utilize CPUs in other groups. While dependent on the specifics of workload, there's usually a noticeable penalty in crossing L3 boundaries, so let's default to CACHE. This issue will be further addressed and documented with examples in future patches. Signed-off-by: Tejun Heo

workqueue: Generalize unbound CPU pods

2023-08-08T01:57:24Z

While renamed to pod, the code still assumes that the pods are defined by NUMA boundaries. Let's generalize it: * workqueue_attrs->affn_scope is added. Each enum represents the type of boundaries that define the pods. There are currently two scopes - WQ_AFFN_NUMA and WQ_AFFN_SYSTEM. The former is the same behavior as before - one pod per NUMA node. The latter defines one global pod across the whole system. * struct wq_pod_type is added which describes how pods are configured for each affnity scope. For each pod, it lists the member CPUs and the preferred NUMA node for memory allocations. The reverse mapping from CPU to pod is also available. * wq_pod_enabled is dropped. Pod is now always enabled. The previously disabled behavior is now implemented through WQ_AFFN_SYSTEM. * get_unbound_pool() wants to determine the NUMA node to allocate memory from for the new pool. The variables are renamed from node to pod but the logic still assumes they're one and the same. Clearly distinguish them - walk the WQ_AFFN_NUMA pods to find the matching pod and then use the pod's NUMA node. * wq_calc_pod_cpumask() was taking @pod but assumed that it was the NUMA node. Take @cpu instead and determine the cpumask to use from the pod_type matching @attrs. * apply_wqattrs_prepare() is update to return ERR_PTR() on error instead of NULL so that it can indicate -EINVAL on invalid affinity scopes. This patch allows CPUs to be grouped into pods however desired per type. While this patch causes some internal behavior changes, nothing material should change for workqueue users. v2: Trigger WARN_ON_ONCE() in wqattrs_pod_type() if affn_scope is WQ_AFFN_NR_TYPES which indicates that the function is called with a worker_pool's attrs instead of a workqueue's. Signed-off-by: Tejun Heo

workqueue: Initialize unbound CPU pods later in the boot

2023-08-08T01:57:24Z

During boot, to initialize unbound CPU pods, wq_pod_init() was called from workqueue_init(). This is early enough for NUMA nodes to be set up but before SMP is brought up and CPU topology information is populated. Workqueue is in the process of improving CPU locality for unbound workqueues and will need access to topology information during pod init. This adds a new init function workqueue_init_topology() which is called after CPU topology information is available and replaces wq_pod_init(). As unbound CPU pods are now initialized after workqueues are activated, we need to revisit the workqueues to apply the pod configuration. Workqueues which are created before workqueue_init_topology() are set up so that they always use the default worker pool. After pods are set up in workqueue_init_topology(), wq_update_pod() is called on all existing workqueues to update the pool associations accordingly. Note that wq_update_pod_attrs_buf allocation is moved to workqueue_init_early(). This isn't necessary right now but enables further generalization of pod handling in the future. This patch changes the initialization sequence but the end result should be the same. Signed-off-by: Tejun Heo

workqueue: Rename workqueue_attrs->no_numa to ->ordered

2023-08-08T01:57:23Z

With the recent removal of NUMA related module param and sysfs knob, workqueue_attrs->no_numa is now only used to implement ordered workqueues. Let's rename the field so that it's less confusing especially with the planned CPU affinity awareness improvements. Just a rename. No functional changes. Signed-off-by: Tejun Heo

workqueue: Make unbound workqueues to use per-cpu pool_workqueues

2023-08-08T01:57:23Z

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 Acked-by: Dennis Dalessandro Cc: Jason Gunthorpe Cc: Leon Romanovsky Cc: Karsten Graul Cc: Wenjia Zhang Cc: Jan Karcher

workqueue: Warn attempt to flush system-wide workqueues.

2023-07-10T20:39:17Z

Based on commit c4f135d643823a86 ("workqueue: Wrap flush_workqueue() using a macro"), all in-tree users stopped flushing system-wide workqueues. Therefore, start emitting runtime message so that all out-of-tree users will understand that they need to update their code. Signed-off-by: Tetsuo Handa Signed-off-by: Tejun Heo