Work with Complex Numbers on a GPU
You can accelerate many functions in MATLAB® that operate on or return complex numbers by using a GPU. This page
describes the conditions you should be aware of when you work with complex numbers and
your data is a gpuArray. For information about handling complex data in
your custom CUDA® code running in MATLAB instead, see Run MEX Functions Containing CUDA Code.
Conditions for Working with Complex Numbers on a GPU
If the output of a function running on a GPU could potentially be complex, you
must explicitly specify its input arguments as complex using the complex function. This applies to
functions operating on gpuArray objects directly and to
functions operating on gpuArray data using arrayfun.
For example, to successfully compute sqrt(G) where
G is a gpuArray containing negative
elements, specify that G is complex.
x = [-1 0 1]; G = gpuArray(complex(x)); rootG = sqrt(G)
0.0000 + 1.0000i 0.0000 + 0.0000i 1.0000 + 0.0000i
If the result is a gpuArray of complex data and all the
imaginary parts are zero, these parts are retained and the data remains complex.
This could result in unnecessary calculations being performed when operating on the
data using, for example, sort and
isreal.
When you use arrayfun to apply functions whose outputs could
potentially be complex, specify the function input as complex within the
arrayfun call.
x = [-1 0 1]; G = gpuArray(x); A = arrayfun(@(p) sqrt(complex(p)),G)
0.0000 + 1.0000i 0.0000 + 0.0000i 1.0000 + 0.0000i
Functions That Return Complex Data
This table lists the functions that might return complex data, along with the input range over which the output remains real.
