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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 10:05:51 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 10:05:51 +0000 |
commit | 5d1646d90e1f2cceb9f0828f4b28318cd0ec7744 (patch) | |
tree | a94efe259b9009378be6d90eb30d2b019d95c194 /Documentation/core-api/padata.rst | |
parent | Initial commit. (diff) | |
download | linux-430c2fc249ea5c0536abd21c23382884005c9093.tar.xz linux-430c2fc249ea5c0536abd21c23382884005c9093.zip |
Adding upstream version 5.10.209.upstream/5.10.209upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'Documentation/core-api/padata.rst')
-rw-r--r-- | Documentation/core-api/padata.rst | 178 |
1 files changed, 178 insertions, 0 deletions
diff --git a/Documentation/core-api/padata.rst b/Documentation/core-api/padata.rst new file mode 100644 index 000000000..35175710b --- /dev/null +++ b/Documentation/core-api/padata.rst @@ -0,0 +1,178 @@ +.. SPDX-License-Identifier: GPL-2.0 + +======================================= +The padata parallel execution mechanism +======================================= + +:Date: May 2020 + +Padata is a mechanism by which the kernel can farm jobs out to be done in +parallel on multiple CPUs while optionally retaining their ordering. + +It was originally developed for IPsec, which needs to perform encryption and +decryption on large numbers of packets without reordering those packets. This +is currently the sole consumer of padata's serialized job support. + +Padata also supports multithreaded jobs, splitting up the job evenly while load +balancing and coordinating between threads. + +Running Serialized Jobs +======================= + +Initializing +------------ + +The first step in using padata to run serialized jobs is to set up a +padata_instance structure for overall control of how jobs are to be run:: + + #include <linux/padata.h> + + struct padata_instance *padata_alloc(const char *name); + +'name' simply identifies the instance. + +Then, complete padata initialization by allocating a padata_shell:: + + struct padata_shell *padata_alloc_shell(struct padata_instance *pinst); + +A padata_shell is used to submit a job to padata and allows a series of such +jobs to be serialized independently. A padata_instance may have one or more +padata_shells associated with it, each allowing a separate series of jobs. + +Modifying cpumasks +------------------ + +The CPUs used to run jobs can be changed in two ways, programatically with +padata_set_cpumask() or via sysfs. The former is defined:: + + int padata_set_cpumask(struct padata_instance *pinst, int cpumask_type, + cpumask_var_t cpumask); + +Here cpumask_type is one of PADATA_CPU_PARALLEL or PADATA_CPU_SERIAL, where a +parallel cpumask describes which processors will be used to execute jobs +submitted to this instance in parallel and a serial cpumask defines which +processors are allowed to be used as the serialization callback processor. +cpumask specifies the new cpumask to use. + +There may be sysfs files for an instance's cpumasks. For example, pcrypt's +live in /sys/kernel/pcrypt/<instance-name>. Within an instance's directory +there are two files, parallel_cpumask and serial_cpumask, and either cpumask +may be changed by echoing a bitmask into the file, for example:: + + echo f > /sys/kernel/pcrypt/pencrypt/parallel_cpumask + +Reading one of these files shows the user-supplied cpumask, which may be +different from the 'usable' cpumask. + +Padata maintains two pairs of cpumasks internally, the user-supplied cpumasks +and the 'usable' cpumasks. (Each pair consists of a parallel and a serial +cpumask.) The user-supplied cpumasks default to all possible CPUs on instance +allocation and may be changed as above. The usable cpumasks are always a +subset of the user-supplied cpumasks and contain only the online CPUs in the +user-supplied masks; these are the cpumasks padata actually uses. So it is +legal to supply a cpumask to padata that contains offline CPUs. Once an +offline CPU in the user-supplied cpumask comes online, padata is going to use +it. + +Changing the CPU masks are expensive operations, so it should not be done with +great frequency. + +Running A Job +------------- + +Actually submitting work to the padata instance requires the creation of a +padata_priv structure, which represents one job:: + + struct padata_priv { + /* Other stuff here... */ + void (*parallel)(struct padata_priv *padata); + void (*serial)(struct padata_priv *padata); + }; + +This structure will almost certainly be embedded within some larger +structure specific to the work to be done. Most of its fields are private to +padata, but the structure should be zeroed at initialisation time, and the +parallel() and serial() functions should be provided. Those functions will +be called in the process of getting the work done as we will see +momentarily. + +The submission of the job is done with:: + + int padata_do_parallel(struct padata_shell *ps, + struct padata_priv *padata, int *cb_cpu); + +The ps and padata structures must be set up as described above; cb_cpu +points to the preferred CPU to be used for the final callback when the job is +done; it must be in the current instance's CPU mask (if not the cb_cpu pointer +is updated to point to the CPU actually chosen). The return value from +padata_do_parallel() is zero on success, indicating that the job is in +progress. -EBUSY means that somebody, somewhere else is messing with the +instance's CPU mask, while -EINVAL is a complaint about cb_cpu not being in the +serial cpumask, no online CPUs in the parallel or serial cpumasks, or a stopped +instance. + +Each job submitted to padata_do_parallel() will, in turn, be passed to +exactly one call to the above-mentioned parallel() function, on one CPU, so +true parallelism is achieved by submitting multiple jobs. parallel() runs with +software interrupts disabled and thus cannot sleep. The parallel() +function gets the padata_priv structure pointer as its lone parameter; +information about the actual work to be done is probably obtained by using +container_of() to find the enclosing structure. + +Note that parallel() has no return value; the padata subsystem assumes that +parallel() will take responsibility for the job from this point. The job +need not be completed during this call, but, if parallel() leaves work +outstanding, it should be prepared to be called again with a new job before +the previous one completes. + +Serializing Jobs +---------------- + +When a job does complete, parallel() (or whatever function actually finishes +the work) should inform padata of the fact with a call to:: + + void padata_do_serial(struct padata_priv *padata); + +At some point in the future, padata_do_serial() will trigger a call to the +serial() function in the padata_priv structure. That call will happen on +the CPU requested in the initial call to padata_do_parallel(); it, too, is +run with local software interrupts disabled. +Note that this call may be deferred for a while since the padata code takes +pains to ensure that jobs are completed in the order in which they were +submitted. + +Destroying +---------- + +Cleaning up a padata instance predictably involves calling the two free +functions that correspond to the allocation in reverse:: + + void padata_free_shell(struct padata_shell *ps); + void padata_free(struct padata_instance *pinst); + +It is the user's responsibility to ensure all outstanding jobs are complete +before any of the above are called. + +Running Multithreaded Jobs +========================== + +A multithreaded job has a main thread and zero or more helper threads, with the +main thread participating in the job and then waiting until all helpers have +finished. padata splits the job into units called chunks, where a chunk is a +piece of the job that one thread completes in one call to the thread function. + +A user has to do three things to run a multithreaded job. First, describe the +job by defining a padata_mt_job structure, which is explained in the Interface +section. This includes a pointer to the thread function, which padata will +call each time it assigns a job chunk to a thread. Then, define the thread +function, which accepts three arguments, ``start``, ``end``, and ``arg``, where +the first two delimit the range that the thread operates on and the last is a +pointer to the job's shared state, if any. Prepare the shared state, which is +typically allocated on the main thread's stack. Last, call +padata_do_multithreaded(), which will return once the job is finished. + +Interface +========= + +.. kernel-doc:: include/linux/padata.h +.. kernel-doc:: kernel/padata.c |