Module Parmap


module Parmap: sig .. end
Module Parmap: efficient parallel map, fold and mapfold on lists and arrays on multicores.

All the primitives allow to control the granularity of the parallelism via an optional parameter chunksize: if chunksize is omitted, the input sequence is split evenly among the available cores; if chunksize is specified, the input data is split in chunks of size chunksize and dispatched to the available cores using an on demand strategy that ensures automatic load balancing.

A specific primitive array_float_parmap is provided for fast operations on float arrays.



Setting and getting the default value for ncores

val set_default_ncores : int -> unit
val get_default_ncores : unit -> int

Sequence type, subsuming lists and arrays


type 'a sequence =
| L of 'a list
| A of 'a array

The parmapfold, parfold and parmap generic functions, for efficiency reasons, convert the input data into an array internally, so we provide the 'a sequence type to allow passing an array directly as input. If you want to perform a parallel map operation on an array, use array_parmap or array_float_parmap instead.

Parallel mapfold

val parmapfold : ?ncores:int ->
?chunksize:int ->
('a -> 'b) ->
'a sequence -> ('b -> 'c -> 'c) -> 'c -> ('c -> 'c -> 'c) -> 'c
parmapfold ~ncores:n f (L l) op b concat computes List.fold_right op (List.map f l) b by forking n processes on a multicore machine. You need to provide the extra concat operator to combine the partial results of the fold computed on each core. If 'b = 'c, then concat may be simply op. The order of computation in parallel changes w.r.t. sequential execution, so this function is only correct if op and concat are associative and commutative. If the optional chunksize parameter is specified, the processes compute the result in an on-demand fashion on blocks of size chunksize. parmapfold ~ncores:n f (A a) op b concat computes Array.fold_right op (Array.map f a) b

Parallel fold

val parfold : ?ncores:int ->
?chunksize:int ->
('a -> 'b -> 'b) -> 'a sequence -> 'b -> ('b -> 'b -> 'b) -> 'b
parfold ~ncores:n op (L l) b concat computes List.fold_right op l b by forking n processes on a multicore machine. You need to provide the extra concat operator to combine the partial results of the fold computed on each core. If 'b = 'c, then concat may be simply op. The order of computation in parallel changes w.r.t. sequential execution, so this function is only correct if op and concat are associative and commutative. If the optional chunksize parameter is specified, the processes compute the result in an on-demand fashion on blocks of size chunksize. parfold ~ncores:n op (A a) b concat similarly computes Array.fold_right op a b.

Parallel map

val parmap : ?ncores:int -> ?chunksize:int -> ('a -> 'b) -> 'a sequence -> 'b list
parmap ~ncores:n f (L l) computes List.map f l by forking n processes on a multicore machine. parmap ~ncores:n f (A a) computes Array.map f a by forking n processes on a multicore machine. If the optional chunksize parameter is specified, the processes compute the result in an on-demand fashion on blocks of size chunksize; this provides automatic load balancing for unbalanced computations, but the order of the result is no longer guaranteed to be preserved.

Parallel iteration

val pariter : ?ncores:int -> ?chunksize:int -> ('a -> unit) -> 'a sequence -> unit
pariter ~ncores:n f (L l) computes List.iter f l by forking n processes on a multicore machine. parmap ~ncores:n f (A a) computes Array.iter f a by forking n processes on a multicore machine. If the optional chunksize parameter is specified, the processes perform the computation in an on-demand fashion on blocks of size chunksize; this provides automatic load balancing for unbalanced computations.

Parallel mapfold, indexed

val parmapifold : ?ncores:int ->
?chunksize:int ->
(int -> 'a -> 'b) ->
'a sequence -> ('b -> 'c -> 'c) -> 'c -> ('c -> 'c -> 'c) -> 'c
Like parmapfold, but the map function gets as an extra argument the index of the mapped element

Parallel map, indexed

val parmapi : ?ncores:int ->
?chunksize:int -> (int -> 'a -> 'b) -> 'a sequence -> 'b list
Like parmap, but the map function gets as an extra argument the index of the mapped element

Parallel iteration, indexed

val pariteri : ?ncores:int ->
?chunksize:int -> (int -> 'a -> unit) -> 'a sequence -> unit
Like pariter, but the iterated function gets as an extra argument the index of the sequence element

Parallel map on arrays

val array_parmap : ?ncores:int -> ?chunksize:int -> ('a -> 'b) -> 'a array -> 'b array
array_parmap ~ncores:n f a computes Array.map f a by forking n processes on a multicore machine. If the optional chunksize parameter is specified, the processes compute the result in an on-demand fashion on blochs of size chunksize; this provides automatic load balancing for unbalanced computations, but the order of the result is no longer guaranteed to be preserved.

Parallel map on arrays, indexed

val array_parmapi : ?ncores:int -> ?chunksize:int -> (int -> 'a -> 'b) -> 'a array -> 'b array
Like array_parmap, but the map function gets as an extra argument the index of the mapped element

Parallel map on float arrays

exception WrongArraySize
type buf 
val init_shared_buffer : float array -> buf
init_shared_buffer a creates a new memory mapped shared buffer big enough to hold a float array of the size of a. This buffer can be reused in a series of calls to array_float_parmap, avoiding the cost of reallocating it each time.
val array_float_parmap : ?ncores:int ->
?chunksize:int ->
?result:float array ->
?sharedbuffer:buf -> ('a -> float) -> 'a array -> float array
array_float_parmap ~ncores:n f a computes Array.map f a by forking n processes on a multicore machine, and preallocating the resulting array as shared memory, which allows significantly more efficient computation than calling the generic array_parmap function. If the optional chunksize parameter is specified, the processes compute the result in an on-demand fashion on blochs of size chunksize; this provides automatic load balancing for unbalanced computations, *and* the order of the result is still guaranteed to be preserved.

In case you already have at hand an array where to store the result, you can squeeze out some more cpu cycles by passing it as optional parameter result: this will avoid the creation of a result array, which can be costly for very large data sets. Raises WrongArraySize if result is too small to hold the data.

It is possible to share the same preallocated shared memory space across calls, by initialising the space calling init_shared_buffer a and passing the result as the optional sharedbuffer parameter to each subsequent call to array_float_parmap. Raises WrongArraySize if sharedbuffer is too small to hold the input data.


Parallel map on float arrays, indexed

val array_float_parmapi : ?ncores:int ->
?chunksize:int ->
?result:float array ->
?sharedbuffer:buf -> (int -> 'a -> float) -> 'a array -> float array

Like array_float_parmap, but the map function gets as an extra argument the index of the mapped element

Debugging

val debugging : bool -> unit

Enable or disable debugging code in the library; default: false

Redirection of stdout and stderr

val redirecting : bool -> unit

Enable or disable the redirection of the stdout and stderr. If enabled, the stdin and stdout in the workers will be redirected to files located in the temporary directory /tmp, carrying names of the shape .parmap.XXXXX; default: false