Use two bsxfun for row and column vector to span matrix without putting in memory

Hello, I have a vector A of size 1xN and a vector B of size MxN I can span a MxN matrix temp with temp=bsxfun(@times,A,B);. Now the tricky part. I create this temp matrix to multiply the following to my data matrix:

data=data.*exp(1i.*temp);

Is there a way I can use bsxfun to directly apply this operation on data, without creating the large temp matrix in the memory?

Thanks

[dpb]

bsxfun created the temp in memory behind scenes anyway, so it didn't actually save memory in computation, just was transparent in not having the explicit temp variable.

Beginning w/ R2016b implicit expansion was introduced that will replace most uses of bsxfun with more efficient memory usage. If you have a release of that vintage or newer investigate that feature.

Answer 1

[Jan]

A    = rand(1, 1e5);
B    = rand(100, 1e5);
data = ones(size(B));

tic, for k = 1:5
  temp = bsxfun(@times, A, B);
  data = data .* exp(1i .* temp);
end, toc

tic, for k = 1:5
  temp = bsxfun(@times, 1i * A, B);
  data = data .* exp(temp);
end, toc

tic, for k = 1:5
  data = data .* exp((1i * A) .* B);  % Auto-expanding in >= R2016b
end, toc

 Elapsed time is 2.421372 seconds.
 Elapsed time is 2.857152 seconds.
 Elapsed time is 2.136714 seconds.

Observation from the profiler:

data = data .* exp(1i .* temp);

takes the same time as

data = data .* exp(temp);

but

temp = bsxfun(@times, 1i * A, B);

or

temp = 1i * bsxfun(@times, A, B);

have 100% more runtime than

temp = bsxfun(@times, A, B);

If this piece of code is the bottleneck of your code, create C-Mex function.