How to vectorize a for loop but with conditionals inside it ?

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nah
nah 2013-9-20
How to vectorize a for loop but with conditionals in it ?
[sizMat1 sizMat2] = size(matrixToMultiply);
cumulMatProduct = ones(sizMat1,1); %stores the cumulative Products of chosen Matrices.
%gets updated at every iteration
for ix = 2:length(col1)
% Depending on if the value is either 0 or 1, pick a matrix;
if (col1(ix) == 0 )
cumulProduct = simpleMatrix0 * cumulMatrixProduct;
matrixToMultiply = matrix1;
elseif (col1(ix) == 1 )
matrixToMultiply = matrix2;
end
anotherMatrixtoMultiply = diag( exp(constantMatrix) * col2(ix) );
% Another Matrix is created by multiplying a scalar
%(picked from the same index ix of a different column col2 having same dimensions as col1)
cumulMatrixProduct = matrixToMultiply*anotherMatrixtoMultiply*cumulMatrixProduct;
end
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Jan
Jan 2013-9-20
编辑：Jan 2013-9-20
@Readers: Is there a faster was to calculate A * diag(x) * B? I cannot test if A * bsxfun(@times, x, B) is faster than the BLAS librarie's DGEMM with the full matrix.
nah
nah 2013-9-23
Yes, the above test Data with rand should work. If needed, I can post my data as well (possibly by email or git )

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回答（1 个）

Jan
Jan 2013-9-20
编辑：Jan 2013-9-21
I assume that the bottleneck of your code is: exp(constantMatrix), because exp() is very expensive. So move this calculation out of the loops:
expConstantMatrix = exp(constantMatrix);
for ix = 2:length(col1)
...
anotherMatrixtoMultiply = diag( expConstantMatrix * col2(ix) );
Is this really wanted:
if (col1(ix) == 0 )
...
elseif (col1(ix) == 1 )
...
end
Or do you mean
if col1(ix) == 0
...
else
...
end
This might be the same in a standard case, but it is prone to bugs to add an elseif without an else.
[EDITED] Some tests show that this is faster:
anotherVectortoMultiply = expConstantMatrix * col2(ix);
cumulMatrixProduct = matrixToMultiply * bsxfun(@times, anotherVectortoMultiply, cumulMatrixProduct);
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Jan
Jan 2013-9-23
If the multiplications of the matrices are the main work, a vectorization of the loop will not be useful. If large temporary arrays must be created, vectorized code can be slower than the loops. So do not try to optimize code, which is not the bottleneck.
nah
nah 2013-9-24
Actually, the motivation was not to optimize this particular piece, but rather be able to do it in a parallel fashion especially as gpuArray for which converting vectorized code is easier than working with for loops. ( i have a parfor version of the code above, but getting to do such calculations en masse on GPUs is where am stuck )

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