Initializing¶

The first step in using padata to run serialized jobs is to set up apadata_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 suchjobs to be serialized independently. A padata_instance may have one or morepadata_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, programmatically withpadata_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 aparallel cpumask describes which processors will be used to execute jobssubmitted to this instance in parallel and a serial cpumask defines whichprocessors 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’slive in /sys/kernel/pcrypt/<instance-name>. Within an instance’s directorythere are two files, parallel_cpumask and serial_cpumask, and either cpumaskmay 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 bedifferent from the ‘usable’ cpumask.

Padata maintains two pairs of cpumasks internally, the user-supplied cpumasksand the ‘usable’ cpumasks. (Each pair consists of a parallel and a serialcpumask.) The user-supplied cpumasks default to all possible CPUs on instanceallocation and may be changed as above. The usable cpumasks are always asubset of the user-supplied cpumasks and contain only the online CPUs in theuser-supplied masks; these are the cpumasks padata actually uses. So it islegal to supply a cpumask to padata that contains offline CPUs. Once anoffline CPU in the user-supplied cpumask comes online, padata is going to useit.

Changing the CPU masks are expensive operations, so it should not be done withgreat frequency.

Running A Job¶

Actually submitting work to the padata instance requires the creation of apadata_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 largerstructure specific to the work to be done. Most of its fields are private topadata, but the structure should be zeroed at initialisation time, and theparallel() andserial() functions should be provided. Those functions willbe called in the process of getting the work done as we will seemomentarily.

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_cpupoints to the preferred CPU to be used for the final callback when the job isdone; it must be in the current instance’s CPU mask (if not the cb_cpu pointeris updated to point to the CPU actually chosen). The return value frompadata_do_parallel() is zero on success, indicating that the job is inprogress. -EBUSY means that somebody, somewhere else is messing with theinstance’s CPU mask, while -EINVAL is a complaint about cb_cpu not being in theserial cpumask, no online CPUs in the parallel or serial cpumasks, or a stoppedinstance.

Each job submitted topadata_do_parallel() will, in turn, be passed toexactly one call to the above-mentionedparallel() function, on one CPU, sotrue parallelism is achieved by submitting multiple jobs.parallel() runs withsoftware interrupts disabled and thus cannot sleep. Theparallel()function gets the padata_priv structure pointer as its lone parameter;information about the actual work to be done is probably obtained by usingcontainer_of() to find the enclosing structure.

Note thatparallel() has no return value; the padata subsystem assumes thatparallel() will take responsibility for the job from this point. The jobneed not be completed during this call, but, ifparallel() leaves workoutstanding, it should be prepared to be called again with a new job beforethe previous one completes.

Serializing Jobs¶

When a job does complete,parallel() (or whatever function actually finishesthe 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 theserial() function in the padata_priv structure. That call will happen onthe CPU requested in the initial call topadata_do_parallel(); it, too, isrun with local software interrupts disabled.Note that this call may be deferred for a while since the padata code takespains to ensure that jobs are completed in the order in which they weresubmitted.

Destroying¶

Cleaning up a padata instance predictably involves calling the two freefunctions 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 completebefore any of the above are called.