Provided by: libparmap-ocaml-dev_1.0~rc7-1_amd64 
NAME
Parmap - Module Parmap: efficient parallel map, fold and mapfold on lists and arrays on
multicores.
Module
Module Parmap
Documentation
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. ===
=== 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. ===
=== Optional init and finalize functions ===
=== 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. ===
=== Optional init and finalize functions ===
=== The optional 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.).
===
=== 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. ===
=== Optional init and finalize functions ===
=== The optional 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.).
===
=== Parallel mapfold ===
val parmapfold : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 : ?init:(int -> unit) -> ?finalize:(unit -> unit) -> ?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 ===
=== 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 ===
=== Enable or disable debugging code in the library; default: false ===
=== Helper function for redirection of stdout and stderr ===
val redirect : ?path:string -> id:int -> unit
=== Helper function that redirects stdout and stderr to files located in the directory
path, 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. ===