# How to speed up convolution with a million data points

조회 수: 11 (최근 30일)
Runzi Hao 2024년 5월 3일
편집: Runzi Hao 2024년 5월 6일
I am currently doing convolution using nested for loops, for 10^6 data points in each for loop. Are there ways to speed up the following code? Thanks in advance!
% nIters = 40;
% n = 1e6;
% mzL = rand(nIters, n);
% gg = rand(1, n);
mzR_temp = zeros(nIters, 1);
for c = 1:n
mzR_temp(:) = 0;
for d = 1:c
mzR_temp(:) = mzR_temp(:) + gg(c-d+1) * mzL(:,d);
end
mzR_II(:,c) = mzR_temp;
end

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### 채택된 답변

Matt J 2024년 5월 3일
편집: Matt J 2024년 5월 3일
Use conv,
mzR_II=conv(gg,mzL,'same');
or FFTs,
mzR_II=ifft( fft(gg,2*n) .* fft(mzL,2*n) , 'symmetric');
mzR_II=mzR_II(1:n);
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Matt J 2024년 5월 3일
편집: Matt J 2024년 5월 3일
There is absolutely no way the computation should take more than 1 second on any computer made within the last 10 years.
n=1e6;
mzL = rand(1,n);
gg = rand(1,n-1);
tic
mzR_II = [0 fftfilt(mzL,gg)];
toc
Elapsed time is 0.174552 seconds.
tic;
mzR_II=ifft( fft(gg,2*n) .* fft(mzL,2*n) , 'symmetric');
mzR_II=mzR_II(1:n);
toc
Elapsed time is 0.145911 seconds.
Runzi Hao 2024년 5월 6일
Awesome! Thanks for the suggestion of using fftfilt.
It turns out that, on my computer, the convolution ran 43 s for a million data points; and with 40 iterations, the total time was 2600+ s. However, the fftfilt function ran only 8 s for the 40 million data points!

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### 추가 답변 (1개)

Image Analyst 2024년 5월 3일
Use the built-in convolutions functions: conv and conv2. They are highly optimized for speed.

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