GPU performance with short vectors

Hello - I see GPU computation underperforming when used for vector manipulation with short lengths.
>> a = rand(1000000, 100,'gpuArray');
>> b= gather(a);
>> tic; for i=1:100 ; eval('q = zeros(1000000,1);for i = 1:100; q = b(:,i)+q;end') ; end;doc
Elapsed time is 45.489811 seconds.
>>tic; for i=1:100 ; eval('qq = zeros(1000000,1);for i = 1:100; q = a(:,i)+q;end') ; end;toc
Elapsed time is 0.875140 seconds.
same when done for short vectors see GPU computation under performing:
>> a = rand(200, 100,'gpuArray');
>>b= gather(a);
>> tic; for i=1:100 ; eval('q = zeros(200,1);for i = 1:100; q = b(:,i)+q;end') ; end;doc
Elapsed time is 0.021727 seconds.
>>tic; for i=1:100 ; eval('qq = zeros(200,1);for i = 1:100; q = a(:,i)+q;end') ; end;toc
Elapsed time is 0.833865 seconds.
Any insight will be appreciated.
Thank you.

 采纳的回答

Computation in a GPU core is significantly slower than in a modern CPU core. It makes up for that by having a lot of them - thousands. If you don't give it thousands of things to do at once, you're never going to beat the CPU.
In your simple computation above you are unnecessarily using a loop. This may have been for illustrative purposes, but if it reflects your actual code, you will gain back your performance by removing the loop, i.e.
q = sum(a, [], 2);

更多回答(1 个)

Walter Roberson
Walter Roberson 2016-3-30
Do not use eval() for this. use timeit()

3 个评论

... and for GPU timings, use gputimeit.
Thank you for your insight. time and gputimeit gives very similar results and shows similar trend where smaller vector(a & b above) had worse run performance when run on GPU.

请先登录,再进行评论。

类别

在 帮助中心 和 File Exchange 中查找有关 GPU Computing 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by