Apply function to each page of array on GPU
A = pagefun(FUN,B)
A = pagefun(FUN,B,C,...)
[A,B,...] = pagefun(FUN,C,...)
pagefun iterates over the pages of a gpuArray,
applying the same function to each page.
A = pagefun(FUN,B) applies the function
specified by FUN to each page of the gpuArray B,
and returns the results in gpuArray A, such that A(:,:,I,J,...)
= FUN(B(:,:,I,J,...)). FUN is a handle
to a function that takes a two-dimensional input argument.
You can use gather to retrieve the array
from the GPU back to the MATLAB workspace.
A = pagefun(FUN,B,C,...) evaluates FUN using
pages of the arrays B, C, etc.,
as input arguments with scalar expansion enabled. Any of the input
page dimensions that are scalar are virtually replicated to match
the size of the other arrays in that dimension so that A(:,:,I,J,...)
= FUN(B(:,:,I,J,...), C(:,:,I,J,...),...). At least one
of the inputs B, C, etc. must
be a gpuArray. Any other inputs held in CPU memory are converted
to a gpuArray before calling the function on the GPU. If an array
is to be used in several different pagefun calls,
it is more efficient to convert that array to a gpuArray before your
series of pagefun calls. The input pages B(:,:,I,
J, ...), C(:,:,I, J, ...), etc., must
satisfy all of the input and output requirements of FUN.
[A,B,...] = pagefun(FUN,C,...), where FUN is
a handle to a function that returns multiple outputs, returns gpuArrays
A, B, etc., each corresponding
to one of the output arguments of FUN. pagefun invokes FUN with
as many outputs as there are in the call to pagefun.
All elements of A must be the same class; B can
be a different class from A, but all elements of B must
be of the same class; etc.
FUN must return values of the same class
each time it is called. The order in which pagefun computes
pages is not specified and should not be relied on.
FUN must be a handle to a function that is
written in the MATLAB language (i.e., not a built-in function or a
MEX-function).
Currently the supported values for FUN are:
Most element-wise gpuArray functions, listed in Run Built-In Functions on a GPU, and the following:
@ctranspose
@fliplr
@flipud
@inv
@mldivide
@mrdivide
@mtimes
@rot90
@transpose
M = 3; % output number of rows K = 6; % matrix multiply inner dimension N = 2; % output number of columns P1 = 10; % size of first page dimension P2 = 17; % size of second page dimension P3 = 4; % size of third page dimension P4 = 12; % size of fourth page dimension A = rand(M,K,P1,1,P3,'gpuArray'); B = rand(K,N,1,P2,P3,P4,'gpuArray'); C = pagefun(@mtimes,A,B); s = size(C) % M-by-N-by-P1-by-P2-by-P3-by-P4
s =
3 2 10 17 4 12M = 300; % output number of rows K = 500; % matrix multiply inner dimension N = 1000; % output number of columns P = 200; % number of pages A = rand(M,K,'gpuArray'); B = rand(K,N,P,'gpuArray'); C = pagefun(@mtimes,A,B); s = size(C) % returns M-by-N-by-P
s =
300 1000 200