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Merge branch 'docs-next' of git://git.lwn.net/linux-2.6
* 'docs-next' of git://git.lwn.net/linux-2.6: Add a document describing the padata interface
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@ -250,6 +250,8 @@ numastat.txt
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- info on how to read Numa policy hit/miss statistics in sysfs.
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oops-tracing.txt
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- how to decode those nasty internal kernel error dump messages.
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padata.txt
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- An introduction to the "padata" parallel execution API
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parisc/
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- directory with info on using Linux on PA-RISC architecture.
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parport.txt
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107
Documentation/padata.txt
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107
Documentation/padata.txt
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@ -0,0 +1,107 @@
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The padata parallel execution mechanism
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Last updated for 2.6.34
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Padata is a mechanism by which the kernel can farm work out to be done in
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parallel on multiple CPUs while retaining the ordering of tasks. It was
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developed for use with the IPsec code, which needs to be able to perform
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encryption and decryption on large numbers of packets without reordering
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those packets. The crypto developers made a point of writing padata in a
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sufficiently general fashion that it could be put to other uses as well.
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The first step in using padata is to set up a padata_instance structure for
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overall control of how tasks are to be run:
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#include <linux/padata.h>
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struct padata_instance *padata_alloc(const struct cpumask *cpumask,
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struct workqueue_struct *wq);
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The cpumask describes which processors will be used to execute work
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submitted to this instance. The workqueue wq is where the work will
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actually be done; it should be a multithreaded queue, naturally.
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There are functions for enabling and disabling the instance:
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void padata_start(struct padata_instance *pinst);
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void padata_stop(struct padata_instance *pinst);
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These functions literally do nothing beyond setting or clearing the
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"padata_start() was called" flag; if that flag is not set, other functions
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will refuse to work.
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The list of CPUs to be used can be adjusted with these functions:
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int padata_set_cpumask(struct padata_instance *pinst,
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cpumask_var_t cpumask);
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int padata_add_cpu(struct padata_instance *pinst, int cpu);
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int padata_remove_cpu(struct padata_instance *pinst, int cpu);
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Changing the CPU mask has the look of an expensive operation, though, so it
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probably should not be done with great frequency.
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Actually submitting work to the padata instance requires the creation of a
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padata_priv structure:
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struct padata_priv {
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/* Other stuff here... */
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void (*parallel)(struct padata_priv *padata);
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void (*serial)(struct padata_priv *padata);
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};
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This structure will almost certainly be embedded within some larger
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structure specific to the work to be done. Most its fields are private to
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padata, but the structure should be zeroed at initialization time, and the
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parallel() and serial() functions should be provided. Those functions will
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be called in the process of getting the work done as we will see
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momentarily.
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The submission of work is done with:
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int padata_do_parallel(struct padata_instance *pinst,
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struct padata_priv *padata, int cb_cpu);
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The pinst and padata structures must be set up as described above; cb_cpu
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specifies which CPU will be used for the final callback when the work is
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done; it must be in the current instance's CPU mask. The return value from
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padata_do_parallel() is a little strange; zero is an error return
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indicating that the caller forgot the padata_start() formalities. -EBUSY
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means that somebody, somewhere else is messing with the instance's CPU
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mask, while -EINVAL is a complaint about cb_cpu not being in that CPU mask.
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If all goes well, this function will return -EINPROGRESS, indicating that
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the work is in progress.
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Each task submitted to padata_do_parallel() will, in turn, be passed to
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exactly one call to the above-mentioned parallel() function, on one CPU, so
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true parallelism is achieved by submitting multiple tasks. Despite the
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fact that the workqueue is used to make these calls, parallel() is run with
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software interrupts disabled and thus cannot sleep. The parallel()
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function gets the padata_priv structure pointer as its lone parameter;
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information about the actual work to be done is probably obtained by using
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container_of() to find the enclosing structure.
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Note that parallel() has no return value; the padata subsystem assumes that
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parallel() will take responsibility for the task from this point. The work
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need not be completed during this call, but, if parallel() leaves work
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outstanding, it should be prepared to be called again with a new job before
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the previous one completes. When a task does complete, parallel() (or
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whatever function actually finishes the job) should inform padata of the
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fact with a call to:
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void padata_do_serial(struct padata_priv *padata);
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At some point in the future, padata_do_serial() will trigger a call to the
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serial() function in the padata_priv structure. That call will happen on
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the CPU requested in the initial call to padata_do_parallel(); it, too, is
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done through the workqueue, but with local software interrupts disabled.
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Note that this call may be deferred for a while since the padata code takes
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pains to ensure that tasks are completed in the order in which they were
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submitted.
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The one remaining function in the padata API should be called to clean up
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when a padata instance is no longer needed:
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void padata_free(struct padata_instance *pinst);
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This function will busy-wait while any remaining tasks are completed, so it
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might be best not to call it while there is work outstanding. Shutting
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down the workqueue, if necessary, should be done separately.
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