How do I optimize this code to run efficiently on the GPU?
1 次查看(过去 30 天)
显示 更早的评论
Dear Matlab user,
I try making optimization of function listed below for GPU computing. I try many version of GPU algorithm but look for me that always is GPU slower. I really appreciate any suggestion or help.
%%Declaration of variables
K=4;
C11n = rand(K,508032);
[x1, x2] = size(C11n);
C22b = zeros(x1,x1*(x2/2),'double');
C2 = zeros(K,K,x2/2,'double');
E=eye(x1);
A=reshape(C11n,K,2,x2/2);
AT=permute(A,[2 1 3]);
%%CPU code
tic
for k=1:x2/2
C2(:,:,k)=E-(A(:,:,k)*inv(AT(:,:,k)*A(:,:,k))*AT(:,:,k));
end
toc
%%GPU code
% Declaration of variables
C22 = gpuArray(zeros(K,K,x2/2,'double'));
E=gpuArray(eye(x1));
A=gpuArray(reshape(C11n,K,2,x2/2));
tic
for k=1:x2/2
C22(:,:,k)=E-(A(:,:,k)*inv(AT(:,:,k)*A(:,:,k))*AT(:,:,k));
end
toc
with best regards
Jan
回答(2 个)
Ashish Uthama
2013-11-27
tic
M = pagefun(@mtimes, A(:,:,1:x2/2), AT(:,:,1:x2/2));
M = pagefun(@mtimes, M, M);
C22 = repmat(E,[1 1 x2/2])-M;
toc
I would be curious to know if this works for you, and what times you get on your hardware.
Joss Knight
2013-11-28
编辑:Joss Knight
2013-11-28
Are your matrices always 4x2? This results in AT*A being 2x2, so you can just calculate your inverses manually:
function Ainv = batch2x2inv(A)
% Grab each matrix element as a vector
a = A(1,1,:);
b = A(1,2,:);
c = A(2,1,:);
d = A(2,2,:);
% Compute determinants
det = a.*d - b.*c;
% Construct inverse
Ainv = bsxfun(@rdivide, [d -b; -c a], det);
end
...and the relevant chunk of your code also uses pagefun as Ashish suggests:
AT = pagefun(@transpose, A);
ATA = pagefun(@mtimes, AT, A);
invATA = batch2x2inv(ATA);
pinvA = pagefun(@mtimes, invATA, AT);
residual = pagefun(@mtimes, A, pinvA);
C22 = bsxfun(@minus, E, residual);
Your code now runs 6x faster than the CPU on my machine.
0 个评论
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Parallel Computing Fundamentals 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!