Based on kernel version 4.2. Page generated on 2015-09-09 12:15 EST.
1 2 Concurrency Managed Workqueue (cmwq) 3 4 September, 2010 Tejun Heo <firstname.lastname@example.org> 5 Florian Mickler <email@example.com> 6 7 CONTENTS 8 9 1. Introduction 10 2. Why cmwq? 11 3. The Design 12 4. Application Programming Interface (API) 13 5. Example Execution Scenarios 14 6. Guidelines 15 7. Debugging 16 17 18 1. Introduction 19 20 There are many cases where an asynchronous process execution context 21 is needed and the workqueue (wq) API is the most commonly used 22 mechanism for such cases. 23 24 When such an asynchronous execution context is needed, a work item 25 describing which function to execute is put on a queue. An 26 independent thread serves as the asynchronous execution context. The 27 queue is called workqueue and the thread is called worker. 28 29 While there are work items on the workqueue the worker executes the 30 functions associated with the work items one after the other. When 31 there is no work item left on the workqueue the worker becomes idle. 32 When a new work item gets queued, the worker begins executing again. 33 34 35 2. Why cmwq? 36 37 In the original wq implementation, a multi threaded (MT) wq had one 38 worker thread per CPU and a single threaded (ST) wq had one worker 39 thread system-wide. A single MT wq needed to keep around the same 40 number of workers as the number of CPUs. The kernel grew a lot of MT 41 wq users over the years and with the number of CPU cores continuously 42 rising, some systems saturated the default 32k PID space just booting 43 up. 44 45 Although MT wq wasted a lot of resource, the level of concurrency 46 provided was unsatisfactory. The limitation was common to both ST and 47 MT wq albeit less severe on MT. Each wq maintained its own separate 48 worker pool. A MT wq could provide only one execution context per CPU 49 while a ST wq one for the whole system. Work items had to compete for 50 those very limited execution contexts leading to various problems 51 including proneness to deadlocks around the single execution context. 52 53 The tension between the provided level of concurrency and resource 54 usage also forced its users to make unnecessary tradeoffs like libata 55 choosing to use ST wq for polling PIOs and accepting an unnecessary 56 limitation that no two polling PIOs can progress at the same time. As 57 MT wq don't provide much better concurrency, users which require 58 higher level of concurrency, like async or fscache, had to implement 59 their own thread pool. 60 61 Concurrency Managed Workqueue (cmwq) is a reimplementation of wq with 62 focus on the following goals. 63 64 * Maintain compatibility with the original workqueue API. 65 66 * Use per-CPU unified worker pools shared by all wq to provide 67 flexible level of concurrency on demand without wasting a lot of 68 resource. 69 70 * Automatically regulate worker pool and level of concurrency so that 71 the API users don't need to worry about such details. 72 73 74 3. The Design 75 76 In order to ease the asynchronous execution of functions a new 77 abstraction, the work item, is introduced. 78 79 A work item is a simple struct that holds a pointer to the function 80 that is to be executed asynchronously. Whenever a driver or subsystem 81 wants a function to be executed asynchronously it has to set up a work 82 item pointing to that function and queue that work item on a 83 workqueue. 84 85 Special purpose threads, called worker threads, execute the functions 86 off of the queue, one after the other. If no work is queued, the 87 worker threads become idle. These worker threads are managed in so 88 called worker-pools. 89 90 The cmwq design differentiates between the user-facing workqueues that 91 subsystems and drivers queue work items on and the backend mechanism 92 which manages worker-pools and processes the queued work items. 93 94 There are two worker-pools, one for normal work items and the other 95 for high priority ones, for each possible CPU and some extra 96 worker-pools to serve work items queued on unbound workqueues - the 97 number of these backing pools is dynamic. 98 99 Subsystems and drivers can create and queue work items through special 100 workqueue API functions as they see fit. They can influence some 101 aspects of the way the work items are executed by setting flags on the 102 workqueue they are putting the work item on. These flags include 103 things like CPU locality, concurrency limits, priority and more. To 104 get a detailed overview refer to the API description of 105 alloc_workqueue() below. 106 107 When a work item is queued to a workqueue, the target worker-pool is 108 determined according to the queue parameters and workqueue attributes 109 and appended on the shared worklist of the worker-pool. For example, 110 unless specifically overridden, a work item of a bound workqueue will 111 be queued on the worklist of either normal or highpri worker-pool that 112 is associated to the CPU the issuer is running on. 113 114 For any worker pool implementation, managing the concurrency level 115 (how many execution contexts are active) is an important issue. cmwq 116 tries to keep the concurrency at a minimal but sufficient level. 117 Minimal to save resources and sufficient in that the system is used at 118 its full capacity. 119 120 Each worker-pool bound to an actual CPU implements concurrency 121 management by hooking into the scheduler. The worker-pool is notified 122 whenever an active worker wakes up or sleeps and keeps track of the 123 number of the currently runnable workers. Generally, work items are 124 not expected to hog a CPU and consume many cycles. That means 125 maintaining just enough concurrency to prevent work processing from 126 stalling should be optimal. As long as there are one or more runnable 127 workers on the CPU, the worker-pool doesn't start execution of a new 128 work, but, when the last running worker goes to sleep, it immediately 129 schedules a new worker so that the CPU doesn't sit idle while there 130 are pending work items. This allows using a minimal number of workers 131 without losing execution bandwidth. 132 133 Keeping idle workers around doesn't cost other than the memory space 134 for kthreads, so cmwq holds onto idle ones for a while before killing 135 them. 136 137 For unbound workqueues, the number of backing pools is dynamic. 138 Unbound workqueue can be assigned custom attributes using 139 apply_workqueue_attrs() and workqueue will automatically create 140 backing worker pools matching the attributes. The responsibility of 141 regulating concurrency level is on the users. There is also a flag to 142 mark a bound wq to ignore the concurrency management. Please refer to 143 the API section for details. 144 145 Forward progress guarantee relies on that workers can be created when 146 more execution contexts are necessary, which in turn is guaranteed 147 through the use of rescue workers. All work items which might be used 148 on code paths that handle memory reclaim are required to be queued on 149 wq's that have a rescue-worker reserved for execution under memory 150 pressure. Else it is possible that the worker-pool deadlocks waiting 151 for execution contexts to free up. 152 153 154 4. Application Programming Interface (API) 155 156 alloc_workqueue() allocates a wq. The original create_*workqueue() 157 functions are deprecated and scheduled for removal. alloc_workqueue() 158 takes three arguments - @name, @flags and @max_active. @name is the 159 name of the wq and also used as the name of the rescuer thread if 160 there is one. 161 162 A wq no longer manages execution resources but serves as a domain for 163 forward progress guarantee, flush and work item attributes. @flags 164 and @max_active control how work items are assigned execution 165 resources, scheduled and executed. 166 167 @flags: 168 169 WQ_UNBOUND 170 171 Work items queued to an unbound wq are served by the special 172 woker-pools which host workers which are not bound to any 173 specific CPU. This makes the wq behave as a simple execution 174 context provider without concurrency management. The unbound 175 worker-pools try to start execution of work items as soon as 176 possible. Unbound wq sacrifices locality but is useful for 177 the following cases. 178 179 * Wide fluctuation in the concurrency level requirement is 180 expected and using bound wq may end up creating large number 181 of mostly unused workers across different CPUs as the issuer 182 hops through different CPUs. 183 184 * Long running CPU intensive workloads which can be better 185 managed by the system scheduler. 186 187 WQ_FREEZABLE 188 189 A freezable wq participates in the freeze phase of the system 190 suspend operations. Work items on the wq are drained and no 191 new work item starts execution until thawed. 192 193 WQ_MEM_RECLAIM 194 195 All wq which might be used in the memory reclaim paths _MUST_ 196 have this flag set. The wq is guaranteed to have at least one 197 execution context regardless of memory pressure. 198 199 WQ_HIGHPRI 200 201 Work items of a highpri wq are queued to the highpri 202 worker-pool of the target cpu. Highpri worker-pools are 203 served by worker threads with elevated nice level. 204 205 Note that normal and highpri worker-pools don't interact with 206 each other. Each maintain its separate pool of workers and 207 implements concurrency management among its workers. 208 209 WQ_CPU_INTENSIVE 210 211 Work items of a CPU intensive wq do not contribute to the 212 concurrency level. In other words, runnable CPU intensive 213 work items will not prevent other work items in the same 214 worker-pool from starting execution. This is useful for bound 215 work items which are expected to hog CPU cycles so that their 216 execution is regulated by the system scheduler. 217 218 Although CPU intensive work items don't contribute to the 219 concurrency level, start of their executions is still 220 regulated by the concurrency management and runnable 221 non-CPU-intensive work items can delay execution of CPU 222 intensive work items. 223 224 This flag is meaningless for unbound wq. 225 226 Note that the flag WQ_NON_REENTRANT no longer exists as all workqueues 227 are now non-reentrant - any work item is guaranteed to be executed by 228 at most one worker system-wide at any given time. 229 230 @max_active: 231 232 @max_active determines the maximum number of execution contexts per 233 CPU which can be assigned to the work items of a wq. For example, 234 with @max_active of 16, at most 16 work items of the wq can be 235 executing at the same time per CPU. 236 237 Currently, for a bound wq, the maximum limit for @max_active is 512 238 and the default value used when 0 is specified is 256. For an unbound 239 wq, the limit is higher of 512 and 4 * num_possible_cpus(). These 240 values are chosen sufficiently high such that they are not the 241 limiting factor while providing protection in runaway cases. 242 243 The number of active work items of a wq is usually regulated by the 244 users of the wq, more specifically, by how many work items the users 245 may queue at the same time. Unless there is a specific need for 246 throttling the number of active work items, specifying '0' is 247 recommended. 248 249 Some users depend on the strict execution ordering of ST wq. The 250 combination of @max_active of 1 and WQ_UNBOUND is used to achieve this 251 behavior. Work items on such wq are always queued to the unbound 252 worker-pools and only one work item can be active at any given time thus 253 achieving the same ordering property as ST wq. 254 255 256 5. Example Execution Scenarios 257 258 The following example execution scenarios try to illustrate how cmwq 259 behave under different configurations. 260 261 Work items w0, w1, w2 are queued to a bound wq q0 on the same CPU. 262 w0 burns CPU for 5ms then sleeps for 10ms then burns CPU for 5ms 263 again before finishing. w1 and w2 burn CPU for 5ms then sleep for 264 10ms. 265 266 Ignoring all other tasks, works and processing overhead, and assuming 267 simple FIFO scheduling, the following is one highly simplified version 268 of possible sequences of events with the original wq. 269 270 TIME IN MSECS EVENT 271 0 w0 starts and burns CPU 272 5 w0 sleeps 273 15 w0 wakes up and burns CPU 274 20 w0 finishes 275 20 w1 starts and burns CPU 276 25 w1 sleeps 277 35 w1 wakes up and finishes 278 35 w2 starts and burns CPU 279 40 w2 sleeps 280 50 w2 wakes up and finishes 281 282 And with cmwq with @max_active >= 3, 283 284 TIME IN MSECS EVENT 285 0 w0 starts and burns CPU 286 5 w0 sleeps 287 5 w1 starts and burns CPU 288 10 w1 sleeps 289 10 w2 starts and burns CPU 290 15 w2 sleeps 291 15 w0 wakes up and burns CPU 292 20 w0 finishes 293 20 w1 wakes up and finishes 294 25 w2 wakes up and finishes 295 296 If @max_active == 2, 297 298 TIME IN MSECS EVENT 299 0 w0 starts and burns CPU 300 5 w0 sleeps 301 5 w1 starts and burns CPU 302 10 w1 sleeps 303 15 w0 wakes up and burns CPU 304 20 w0 finishes 305 20 w1 wakes up and finishes 306 20 w2 starts and burns CPU 307 25 w2 sleeps 308 35 w2 wakes up and finishes 309 310 Now, let's assume w1 and w2 are queued to a different wq q1 which has 311 WQ_CPU_INTENSIVE set, 312 313 TIME IN MSECS EVENT 314 0 w0 starts and burns CPU 315 5 w0 sleeps 316 5 w1 and w2 start and burn CPU 317 10 w1 sleeps 318 15 w2 sleeps 319 15 w0 wakes up and burns CPU 320 20 w0 finishes 321 20 w1 wakes up and finishes 322 25 w2 wakes up and finishes 323 324 325 6. Guidelines 326 327 * Do not forget to use WQ_MEM_RECLAIM if a wq may process work items 328 which are used during memory reclaim. Each wq with WQ_MEM_RECLAIM 329 set has an execution context reserved for it. If there is 330 dependency among multiple work items used during memory reclaim, 331 they should be queued to separate wq each with WQ_MEM_RECLAIM. 332 333 * Unless strict ordering is required, there is no need to use ST wq. 334 335 * Unless there is a specific need, using 0 for @max_active is 336 recommended. In most use cases, concurrency level usually stays 337 well under the default limit. 338 339 * A wq serves as a domain for forward progress guarantee 340 (WQ_MEM_RECLAIM, flush and work item attributes. Work items which 341 are not involved in memory reclaim and don't need to be flushed as a 342 part of a group of work items, and don't require any special 343 attribute, can use one of the system wq. There is no difference in 344 execution characteristics between using a dedicated wq and a system 345 wq. 346 347 * Unless work items are expected to consume a huge amount of CPU 348 cycles, using a bound wq is usually beneficial due to the increased 349 level of locality in wq operations and work item execution. 350 351 352 7. Debugging 353 354 Because the work functions are executed by generic worker threads 355 there are a few tricks needed to shed some light on misbehaving 356 workqueue users. 357 358 Worker threads show up in the process list as: 359 360 root 5671 0.0 0.0 0 0 ? S 12:07 0:00 [kworker/0:1] 361 root 5672 0.0 0.0 0 0 ? S 12:07 0:00 [kworker/1:2] 362 root 5673 0.0 0.0 0 0 ? S 12:12 0:00 [kworker/0:0] 363 root 5674 0.0 0.0 0 0 ? S 12:13 0:00 [kworker/1:0] 364 365 If kworkers are going crazy (using too much cpu), there are two types 366 of possible problems: 367 368 1. Something being scheduled in rapid succession 369 2. A single work item that consumes lots of cpu cycles 370 371 The first one can be tracked using tracing: 372 373 $ echo workqueue:workqueue_queue_work > /sys/kernel/debug/tracing/set_event 374 $ cat /sys/kernel/debug/tracing/trace_pipe > out.txt 375 (wait a few secs) 376 ^C 377 378 If something is busy looping on work queueing, it would be dominating 379 the output and the offender can be determined with the work item 380 function. 381 382 For the second type of problems it should be possible to just check 383 the stack trace of the offending worker thread. 384 385 $ cat /proc/THE_OFFENDING_KWORKER/stack 386 387 The work item's function should be trivially visible in the stack 388 trace.