module Parmap:sig..end
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.
val set_default_ncores : int -> unit
val get_default_ncores : unit -> inttype 'a sequence =
| |
L of |
| |
A of |
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.init (resp. finalize) function is called once by each child process just after creation
(resp. just before exit).
init and finalize both default to doing nothing.
init i takes the child rank i as parameter (first forked child has rank 0, next 1, etc.).val parmapfold : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int ->
('a -> 'b) ->
'a sequence -> ('b -> 'c -> 'c) -> 'c -> ('c -> 'c -> 'c) -> 'cparmapfold ~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) bval parfold : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int ->
('a -> 'b -> 'b) -> 'a sequence -> 'b -> ('b -> 'b -> 'b) -> 'bparfold ~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.val parmap : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int -> ?chunksize:int -> ('a -> 'b) -> 'a sequence -> 'b listparmap ~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.val pariter : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int -> ?chunksize:int -> ('a -> unit) -> 'a sequence -> unitpariter ~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.val parmapifold : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int ->
(int -> 'a -> 'b) ->
'a sequence -> ('b -> 'c -> 'c) -> 'c -> ('c -> 'c -> 'c) -> 'cval parmapi : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int -> (int -> 'a -> 'b) -> 'a sequence -> 'b listval pariteri : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int -> (int -> 'a -> unit) -> 'a sequence -> unitval array_parmap : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int -> ?chunksize:int -> ('a -> 'b) -> 'a array -> 'b arrayarray_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.val array_parmapi : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int -> ?chunksize:int -> (int -> 'a -> 'b) -> 'a array -> 'b arrayexception WrongArraySize
type buf
: float array -> bufinit_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 : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int ->
?result:float array ->
?sharedbuffer:buf -> ('a -> float) -> 'a array -> float arrayarray_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.
val array_float_parmapi : ?init:(int -> unit) ->
?finalize:(unit -> unit) ->
?ncores:int ->
?chunksize:int ->
?result:float array ->
?sharedbuffer:buf -> (int -> 'a -> float) -> 'a array -> float arrayval debugging : bool -> unitval redirect : ?path:string -> id:int -> unitpath, carrying names of the shape
stdout.NNN and stderr.NNN where NNN is the id of the used core.
Useful when writing initialisation functions to be passed as
init argument to the parallel combinators.
The default value for path is /tmp/.parmap.PPPP with PPPP the
process id of the main program.