Can this be accelerated?

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Patrick Mboma
Patrick Mboma on 25 Jul 2015
Commented: James Tursa on 26 Jul 2015
Hi,
The following computations are very expensive for large matrices A, B and the coefficient q.
C=reshape(A,a1*q,b1)*B;
C=reshape(C,a1,b2*q);
a1 and a2 are the dimensions of A, while b1 and b2 are the dimensions of B and with the restriction that a2=b1*q.
In my applications, matrices A and B can have dimensions in the orders of thousands or more.
There is one way of implementing these operations using loops
C=zeros(a1,b2*q);
acols=0:q:(b1-1)*q;
ccols=0:q:(b2-1)*q;
for ii=q:-1:1
C(:,ccols+ii)=A(:,acols+ii)*B;
end
but that strategy is not as fast as the one above. Is there any way to accelerate these operations?
try them for instance with the following
b1=1300;
b2=500;
q=350;
a1=300;
a2=b1*q;
B=rand(b1,b2);
A=rand(a1,a2);
Thanks

Accepted Answer

Azzi Abdelmalek
Azzi Abdelmalek on 25 Jul 2015
  4 Comments
Patrick Mboma
Patrick Mboma on 25 Jul 2015
Looks like I may have overlooked something... Thanks for pointing that out.
James Tursa
James Tursa on 26 Jul 2015
Are any of the matrices sparse? For full matrices, reshape is extremely fast since it returns a shared data copy. But for sparse matrices, reshape is expensive since it requires a deep data copy.

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