1.. SPDX-License-Identifier: GPL-2.0 2 3======================================= 4The padata parallel execution mechanism 5======================================= 6 7:Date: May 2020 8 9Padata is a mechanism by which the kernel can farm jobs out to be done in 10parallel on multiple CPUs while optionally retaining their ordering. 11 12It was originally developed for IPsec, which needs to perform encryption and 13decryption on large numbers of packets without reordering those packets. This 14is currently the sole consumer of padata's serialized job support. 15 16Padata also supports multithreaded jobs, splitting up the job evenly while load 17balancing and coordinating between threads. 18 19Running Serialized Jobs 20======================= 21 22Initializing 23------------ 24 25The first step in using padata to run serialized jobs is to set up a 26padata_instance structure for overall control of how jobs are to be run:: 27 28 #include <linux/padata.h> 29 30 struct padata_instance *padata_alloc(const char *name); 31 32'name' simply identifies the instance. 33 34Then, complete padata initialization by allocating a padata_shell:: 35 36 struct padata_shell *padata_alloc_shell(struct padata_instance *pinst); 37 38A padata_shell is used to submit a job to padata and allows a series of such 39jobs to be serialized independently. A padata_instance may have one or more 40padata_shells associated with it, each allowing a separate series of jobs. 41 42Modifying cpumasks 43------------------ 44 45The CPUs used to run jobs can be changed in two ways, programmatically with 46padata_set_cpumask() or via sysfs. The former is defined:: 47 48 int padata_set_cpumask(struct padata_instance *pinst, int cpumask_type, 49 cpumask_var_t cpumask); 50 51Here cpumask_type is one of PADATA_CPU_PARALLEL or PADATA_CPU_SERIAL, where a 52parallel cpumask describes which processors will be used to execute jobs 53submitted to this instance in parallel and a serial cpumask defines which 54processors are allowed to be used as the serialization callback processor. 55cpumask specifies the new cpumask to use. 56 57There may be sysfs files for an instance's cpumasks. For example, pcrypt's 58live in /sys/kernel/pcrypt/<instance-name>. Within an instance's directory 59there are two files, parallel_cpumask and serial_cpumask, and either cpumask 60may be changed by echoing a bitmask into the file, for example:: 61 62 echo f > /sys/kernel/pcrypt/pencrypt/parallel_cpumask 63 64Reading one of these files shows the user-supplied cpumask, which may be 65different from the 'usable' cpumask. 66 67Padata maintains two pairs of cpumasks internally, the user-supplied cpumasks 68and the 'usable' cpumasks. (Each pair consists of a parallel and a serial 69cpumask.) The user-supplied cpumasks default to all possible CPUs on instance 70allocation and may be changed as above. The usable cpumasks are always a 71subset of the user-supplied cpumasks and contain only the online CPUs in the 72user-supplied masks; these are the cpumasks padata actually uses. So it is 73legal to supply a cpumask to padata that contains offline CPUs. Once an 74offline CPU in the user-supplied cpumask comes online, padata is going to use 75it. 76 77Changing the CPU masks are expensive operations, so it should not be done with 78great frequency. 79 80Running A Job 81------------- 82 83Actually submitting work to the padata instance requires the creation of a 84padata_priv structure, which represents one job:: 85 86 struct padata_priv { 87 /* Other stuff here... */ 88 void (*parallel)(struct padata_priv *padata); 89 void (*serial)(struct padata_priv *padata); 90 }; 91 92This structure will almost certainly be embedded within some larger 93structure specific to the work to be done. Most of its fields are private to 94padata, but the structure should be zeroed at initialisation time, and the 95parallel() and serial() functions should be provided. Those functions will 96be called in the process of getting the work done as we will see 97momentarily. 98 99The submission of the job is done with:: 100 101 int padata_do_parallel(struct padata_shell *ps, 102 struct padata_priv *padata, int *cb_cpu); 103 104The ps and padata structures must be set up as described above; cb_cpu 105points to the preferred CPU to be used for the final callback when the job is 106done; it must be in the current instance's CPU mask (if not the cb_cpu pointer 107is updated to point to the CPU actually chosen). The return value from 108padata_do_parallel() is zero on success, indicating that the job is in 109progress. -EBUSY means that somebody, somewhere else is messing with the 110instance's CPU mask, while -EINVAL is a complaint about cb_cpu not being in the 111serial cpumask, no online CPUs in the parallel or serial cpumasks, or a stopped 112instance. 113 114Each job submitted to padata_do_parallel() will, in turn, be passed to 115exactly one call to the above-mentioned parallel() function, on one CPU, so 116true parallelism is achieved by submitting multiple jobs. parallel() runs with 117software interrupts disabled and thus cannot sleep. The parallel() 118function gets the padata_priv structure pointer as its lone parameter; 119information about the actual work to be done is probably obtained by using 120container_of() to find the enclosing structure. 121 122Note that parallel() has no return value; the padata subsystem assumes that 123parallel() will take responsibility for the job from this point. The job 124need not be completed during this call, but, if parallel() leaves work 125outstanding, it should be prepared to be called again with a new job before 126the previous one completes. 127 128Serializing Jobs 129---------------- 130 131When a job does complete, parallel() (or whatever function actually finishes 132the work) should inform padata of the fact with a call to:: 133 134 void padata_do_serial(struct padata_priv *padata); 135 136At some point in the future, padata_do_serial() will trigger a call to the 137serial() function in the padata_priv structure. That call will happen on 138the CPU requested in the initial call to padata_do_parallel(); it, too, is 139run with local software interrupts disabled. 140Note that this call may be deferred for a while since the padata code takes 141pains to ensure that jobs are completed in the order in which they were 142submitted. 143 144Destroying 145---------- 146 147Cleaning up a padata instance predictably involves calling the two free 148functions that correspond to the allocation in reverse:: 149 150 void padata_free_shell(struct padata_shell *ps); 151 void padata_free(struct padata_instance *pinst); 152 153It is the user's responsibility to ensure all outstanding jobs are complete 154before any of the above are called. 155 156Running Multithreaded Jobs 157========================== 158 159A multithreaded job has a main thread and zero or more helper threads, with the 160main thread participating in the job and then waiting until all helpers have 161finished. padata splits the job into units called chunks, where a chunk is a 162piece of the job that one thread completes in one call to the thread function. 163 164A user has to do three things to run a multithreaded job. First, describe the 165job by defining a padata_mt_job structure, which is explained in the Interface 166section. This includes a pointer to the thread function, which padata will 167call each time it assigns a job chunk to a thread. Then, define the thread 168function, which accepts three arguments, ``start``, ``end``, and ``arg``, where 169the first two delimit the range that the thread operates on and the last is a 170pointer to the job's shared state, if any. Prepare the shared state, which is 171typically allocated on the main thread's stack. Last, call 172padata_do_multithreaded(), which will return once the job is finished. 173 174Interface 175========= 176 177.. kernel-doc:: include/linux/padata.h 178.. kernel-doc:: kernel/padata.c 179