Speed up code on GPU by removing nested for loops

2018 10 1
4 个回答
回答已采纳
更新时间：2018 10 11
4 次查看（30 天）

0 个投票

Hello! I'm trying to speed up the following element-by-element array operation using the parallel computing toolbox. Is this a good candidate for arrayfun? What might that look like? Any advice would be greatly appreciated.

for ii = 1:Nx
  for jj = 1:Ny
       f1(ii,jj) = exp(i*pi*(ii + jj));
  end
end

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 采纳的回答

Bruno Luong
Bruno Luong 2018-10-1

0 个投票

f1 = exp((1i*pi) * (ii(:) + jj(:).'));
or on older MATLAB version (without auto expansion).
f1 = exp(bsxfun(@plus, (1i*pi) * ii(:), jj(:).'))
Avoid using ARRAYFUN with you like clear and fast code.

更多回答（3 个）

Noah Walcutt
Noah Walcutt 2018-10-11
编辑：Noah Walcutt 2018-10-11

0 个投票

Another array expansion problem, but slightly different:
for ii = 1:Nx
for jj = 1:Ny
u = delta0*(ii - Nx/2 -1);
v = delta0*(jj - Ny/2 -1);
p(ii,jj) = exp(1i*pi*lambda*z0*(u^2 + v^2));
end
end
Using bsxfun, I've got:
pp = exp(bsxfun(@plus, (1i*pi*lambda*z0*(delta0*(iii - Nx/2 -1)).^2), (jjj - Ny/2 -1).^2) );
What am I doing wrong here?
Noah Walcutt
Noah Walcutt 2018-10-11

0 个投票

Got it!
pp = exp(bsxfun(@plus, (1i*pi*lambda*z0*(delta0*(iii - Nx/2 -1)).^2), (1i*pi*lambda*z0*(delta0*(jjj - Ny/2 -1)).^2)));

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