vectorised code is terribly slower

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Michal 2019-9-9

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https://ww2.mathworks.cn/matlabcentral/answers/479509-vectorised-code-is-terribly-slower

评论： Michal 2019-9-9

Why is the vectorized version of simple local maxima detection code significantly slower (~2-3 times) than its for-loop version?

%ntest data
X = rand(100000,1000);
% findig local maxima over columns of X
% for-loop version
tic;
[I,J] = size(X);
Ind = false(I,J);
for j = 1:J
    Ind(:,j) = diff( sign( diff([0; X(:,j); 0]) ) ) < 0;
end
toc
% vectorized version (~3 times slower than for-loop)
tic;
Ind_ = diff(sign(diff([zeros(1,J);X;zeros(1,J)],1,1)),1,1) < 0;
toc
% result identity test
isequal(Ind,Ind_)

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Bruno Luong 2019-9-9

It is possibly that the DIFF implementation on array does not access sequently memory in case of 2D array data, but row-by-row of the array, that might slow down.

I don't think the multi-threading is wrongly implemented.

Michal 2019-9-9

The main problem is, that during continuous development of JIT engine are alwyas changing MATLAB performance characteristics for vectorized codes. In general, the standard for-loop codes becomes faster and faster.

I have plenty of highly vectorized MATLAB codes created during last 10 years, which are during last few years becomes slower than theirs for-loop counter parts. So, there is no code performance stability.

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