Diagonal matrix size reduction
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Dear All,
I have a loop written for GPU (gpuarrays) with multiple matrix inputs, one of which is a diagonal matrix A with size m (A=eye(m)), with m from 10000-100000. m proves limiting as I get GPU memory errors with higher m values. A is involved in several left and right multiplication steps, and is updated (fills) with each iteration. Is there any matrix decomposition/factorization implementation in matlab that will allow rendering of A as A= a*b (or a*b*c and so on) where a size is (m,n), b size (n,m) etc (n << m) so that I can introduce intermediate code steps using a, b etc in these operations and reduce memory cost? Thank you, as always,
Octavian
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Edric Ellis
il 30 Mar 2015
In R2015a, sparse support was added to gpuArray - perhaps this might help you? mtimes is one of the methods that is implemented for sparse gpuArray.
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