Adding upstream version 5.10.209.upstream/5.10.209upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+.. 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