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


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.


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.


struct padata_priv

Represents one job


struct padata_priv {
  struct list_head        list;
  struct parallel_data    *pd;
  int cb_cpu;
  unsigned int            seq_nr;
  int info;
  void (*parallel)(struct padata_priv *padata);
  void (*serial)(struct padata_priv *padata);


List entry, to attach to the padata lists.
Pointer to the internal control structure.
Callback cpu for serializatioon.
Sequence number of the parallelized data object.
Used to pass information from the parallel to the serial function.
Parallel execution function.
Serial complete function.
struct padata_list

one per work type per CPU


struct padata_list {
  struct list_head        list;
  spinlock_t lock;


List head.
List lock.
struct padata_serial_queue

The percpu padata serial queue


struct padata_serial_queue {
  struct padata_list    serial;
  struct work_struct    work;
  struct parallel_data *pd;


List to wait for serialization after reordering.
work struct for serialization.
Backpointer to the internal control structure.
struct padata_cpumask

The cpumasks for the parallel/serial workers


struct padata_cpumask {
  cpumask_var_t pcpu;
  cpumask_var_t cbcpu;


cpumask for the parallel workers.
cpumask for the serial (callback) workers.
struct parallel_data

Internal control structure, covers everything that depends on the cpumask in use.


struct parallel_data {
  struct padata_shell             *ps;
  struct padata_list              __percpu *reorder_list;
  struct padata_serial_queue      __percpu *squeue;
  atomic_t refcnt;
  unsigned int                    seq_nr;
  unsigned int                    processed;
  int cpu;
  struct padata_cpumask           cpumask;
  struct work_struct              reorder_work;
  spinlock_t ____cacheline_aligned lock;


padata_shell object.
percpu reorder lists
percpu padata queues used for serialuzation.
Number of objects holding a reference on this parallel_data.
Sequence number of the parallelized data object.
Number of already processed objects.
Next CPU to be processed.
The cpumasks in use for parallel and serial workers.
work struct for reordering.
Reorder lock.
struct padata_shell

Wrapper around struct parallel_data, its purpose is to allow the underlying control structure to be replaced on the fly using RCU.


struct padata_shell {
  struct padata_instance          *pinst;
  struct parallel_data __rcu      *pd;
  struct parallel_data            *opd;
  struct list_head                list;


padat instance.
Actual parallel_data structure which may be substituted on the fly.
Pointer to old pd to be freed by padata_replace.
List entry in padata_instance list.
struct padata_mt_job

represents one multithreaded job


struct padata_mt_job {
  void (*thread_fn)(unsigned long start, unsigned long end, void *arg);
  void *fn_arg;
  unsigned long           start;
  unsigned long           size;
  unsigned long           align;
  unsigned long           min_chunk;
  int max_threads;


Called for each chunk of work that a padata thread does.
The thread function argument.
The start of the job (units are job-specific).
size of this node’s work (units are job-specific).
Ranges passed to the thread function fall on this boundary, with the possible exceptions of the beginning and end of the job.
The minimum chunk size in job-specific units. This allows the client to communicate the minimum amount of work that’s appropriate for one worker thread to do at once.
Max threads to use for the job, actual number may be less depending on task size and minimum chunk size.
struct padata_instance

The overall control structure.


struct padata_instance {
  struct hlist_node               cpu_online_node;
  struct hlist_node               cpu_dead_node;
  struct workqueue_struct         *parallel_wq;
  struct workqueue_struct         *serial_wq;
  struct list_head                pslist;
  struct padata_cpumask           cpumask;
  struct kobject                   kobj;
  struct mutex                     lock;
  u8 flags;
#define PADATA_INIT     1;
#define PADATA_RESET    2;
#define PADATA_INVALID  4;


Linkage for CPU online callback.
Linkage for CPU offline callback.
The workqueue used for parallel work.
The workqueue used for serial work.
List of padata_shell objects attached to this instance.
User supplied cpumasks for parallel and serial works.
padata instance kernel object.
padata instance lock.
padata flags.
int padata_do_parallel(struct padata_shell * ps, struct padata_priv * padata, int * cb_cpu)

padata parallelization function


struct padata_shell * ps
struct padata_priv * padata
object to be parallelized
int * cb_cpu
pointer to the CPU that the serialization callback function should run on. If it’s not in the serial cpumask of pinst (i.e. cpumask.cbcpu), this function selects a fallback CPU and if none found, returns -EINVAL.


The parallelization callback function will run with BHs off.


Every object which is parallelized by padata_do_parallel must be seen by padata_do_serial.


0 on success or else negative error code.

void padata_do_serial(struct padata_priv * padata)

padata serialization function


struct padata_priv * padata
object to be serialized.


padata_do_serial must be called for every parallelized object. The serialization callback function will run with BHs off.

void padata_do_multithreaded(struct padata_mt_job * job)

run a multithreaded job


struct padata_mt_job * job
Description of the job.


See the definition of struct padata_mt_job for more details.

int padata_set_cpumask(struct padata_instance * pinst, int cpumask_type, cpumask_var_t cpumask)

Sets specified by cpumask_type cpumask to the value equivalent to cpumask.


struct padata_instance * pinst
padata instance
int cpumask_type
PADATA_CPU_SERIAL or PADATA_CPU_PARALLEL corresponding to parallel and serial cpumasks respectively.
cpumask_var_t cpumask
the cpumask to use


0 on success or negative error code

struct padata_instance * padata_alloc(const char * name)

allocate and initialize a padata instance


const char * name
used to identify the instance


new instance on success, NULL on error

void padata_free(struct padata_instance * pinst)

free a padata instance


struct padata_instance * pinst
padata instance to free
struct padata_shell * padata_alloc_shell(struct padata_instance * pinst)

Allocate and initialize padata shell.


struct padata_instance * pinst
Parent padata_instance object.


new shell on success, NULL on error

void padata_free_shell(struct padata_shell * ps)

free a padata shell


struct padata_shell * ps
padata shell to free