By Jonathan Corbet
April 6, 2010
One day, Andrew Morton was happily reading linux-kernel when he encountered
a patch fixing a minor problem with the "padata" code. Andrew, it seems,
had never heard of padata, which was merged
during the 2.6.34 merge window. So he asked: "
OK, on behalf of
thousands I ask: what the heck is kernel/padata.c?"
On behalf of those same thousands, your editor set out to learn what this
new bit of core kernel code does and how to use it.
In short: padata is a
mechanism by which the kernel can farm work out to be done in parallel on
multiple CPUs while retaining the ordering of tasks. It was developed for
use with the IPsec code, which needs to be able to perform encryption and
decryption on large numbers of packets without reordering those packets.
The crypto developers made a point of writing padata in a sufficiently
general fashion that it could be put to other uses as well, but that
requires knowing that the API is there and how to use it. Unfortunately,
they made a bit less of a point of updating the documentation directory.
The first step in using padata is to set up a padata_instance
structure for overall control of how tasks are to be run:
#include <linux/padata.h>
struct padata_instance *padata_alloc(const struct cpumask *cpumask,
struct workqueue_struct *wq);
The cpumask describes which processors will be used to execute
work submitted to this instance. The workqueue wq is where the
work will actually be done; it should be a multithreaded queue, naturally.
There are functions for enabling and disabling the instance:
void padata_start(struct padata_instance *pinst);
void padata_stop(struct padata_instance *pinst);
These functions literally do nothing beyond setting or clearing the
"padata_start() was called" flag; if that flag is not set, other
functions will refuse to work. There must be some perceived value in this
functionality, but the only current padata user (crypto/pcrypt.c)
does not make use of it. So padata_start() looks like one of
those exercises in pointless bureaucracy that we all have to cope with
sometimes.
The list of CPUs to be used can be adjusted with these functions:
int padata_set_cpumask(struct padata_instance *pinst,
cpumask_var_t cpumask);
int padata_add_cpu(struct padata_instance *pinst, int cpu);
int padata_remove_cpu(struct padata_instance *pinst, int cpu);
Changing the CPU mask has the look of an expensive operation, though, so it
probably should not be done with great frequency.
Actually submitting work to the padata instance requires the creation of a
padata_priv structure:
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 its fields are private to padata, but the
structure should be zeroed at initialization 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 work is done with:
int padata_do_parallel(struct padata_instance *pinst,
struct padata_priv *padata, int cb_cpu);
The pinst and padata structures must be set up as
described above; cb_cpu specifies which CPU will be used for the
final callback when the work is done; it must be in the current instance's
CPU mask. The return value from padata_do_parallel() is a little
strange; zero is an error return indicating that the caller forgot the
padata_start() formalities. -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 that CPU
mask. If all goes well, this function will return -EINPROGRESS,
indicating that the work is in progress.
Each task 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 tasks. The workqueue is used to actually make these calls, so
parallel() runs in process context and is allowed to 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 task from
this point. The work 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.
When a task does complete, parallel() (or whatever function actually
finishes the job) 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 done through the workqueue,
but with local software interrupts disabled.
Note that this call may be deferred for
a while since the padata code takes pains to ensure that tasks are completed in
the order in which they were submitted.
The one remaining function in the padata API should be called to clean up
when a padata instance is no longer needed:
void padata_free(struct padata_instance *pinst);
This function will busy-wait while any remaining tasks are completed, so it
might be best not to call it while there is work outstanding. Shutting
down the workqueue, if necessary, should be done separately.
The API as described above is what can be found in the 2.6.34-rc3 kernel.
As was seen back at the beginning of this article, padata is just coming
into more general awareness, and some developers are asking questions about
the API. So changes are possible - but, then, that is true of any internal
kernel interface.
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