Hi all,
I am calculating the multiplication of matrix and vector using fast
convolution, but this has to be done for many times. Here is a brief framework
of my code:
for(dim=0; dim<NDOF; dim++){ for(i=0; i<NX; i++) { for(j=0;
j<NY; j++) { //compute inpx //compute inpw
//fast convolution } }}
The fast convolution needs to compute multiple times within the for loops. The
dimension of the input vector is 256*256. The most time consuming parts are
MatMult(), VecPoinstwiseMult() and MatMultTranspose() during fast convolution.
The optimal number of processors is 2. Further increase of processor numbers
will reduce the efficiency. In this case, would you please suggest a way to
improve efficiency and fully make use of parallelization? Thanks.
