Binary singleton expansion function for gpuArray
C = bsxfun(FUN,A,B)
bsxfun with gpuArray input is similar in
behavior to the MATLAB® function bsxfun,
except that the actual evaluation of the function, FUN,
happens on the GPU, not on the CPU.
C = bsxfun(FUN,A,B) applies the element-by-element
binary operation specified by the function handle FUN to
arrays A and B, with singleton
expansion enabled. If A or B is
a gpuArray, bsxfun moves all other required data
to the GPU and performs its calculation on the GPU. The output array C is
a gpuArray, which you can copy to the MATLAB workspace with gather.
For more detailed information, see Run Element-wise MATLAB Code on GPU. For the subset of the
MATLAB language that is currently supported by bsxfun on
the GPU, see Supported MATLAB Code.
The corresponding dimensions of A and B must
be equal to each other, or equal to one. Whenever a dimension of A or B is
singleton (equal to 1), bsxfun virtually replicates
the array along that dimension to match the other array. In the case
where a dimension of A or B is
singleton and the corresponding dimension in the other array is zero, bsxfun virtually
diminishes the singleton dimension to 0.
The size of the output array C is such that
each dimension is the larger of the two input arrays in that dimension
for nonzero size, or zero otherwise. Notice in the following code
how dimensions of size 1 are scaled up or down to match the size of
the corresponding dimension in the other argument:
R1 = rand(2,5,4,'gpuArray'); R2 = rand(2,1,4,3,'gpuArray'); R = bsxfun(@plus,R1,R2); size(R)
2 5 4 3
R1 = rand(2,2,0,4,'gpuArray'); R2 = rand(2,1,1,4,'gpuArray'); R = bsxfun(@plus,R1,R2); size(R)
2 2 0 4
Subtract the mean of each column from all elements in that column:
A = rand(8,'gpuArray');
M = bsxfun(@minus,A,mean(A));