Matlab with a Titan Z
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How does Matlab handle the dual-GPU Titan Z? Can you target each individual GPU using something like gpuDevice(1) and gpuDevice(2) (and is it possible to do so in different Matlab sessions)? If not, is it possible to see any performance increase over a single Titan Black (normalizing for clockspeed differences) using a Titan Z as a single gpuDevice?
For specificity, consider the task of repetitively multiplying/adding several large matrices together, eg. something similar to:
% Silly Example Code
for i=1:2000
matrixA = matrixC*matrix1;
matrixB = matrixD*matrix1;
matrix1 = matrix1 + matrixA.*matrixB;
end
Where you might want to do this over multiple completely independent runs (using separate Matlab sessions and compute devices). If a Titan Z was faster than a Titan Black on an individual run or if it could handle two independent runs simultaneously it would be useful. It would only be problematic if the Titan Z wasn't faster than a Titan Black in any respect.
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Accepted Answer
Joss Knight
on 23 Feb 2017
The spec would seem to indicate that each half of a Titan Z is slower than the Titan Black, so it does depend on how you use it as to whether it can be faster.
To use your dual GPU in parallel you can indeed run two separate MATLAB sessions specifying gpuDevice(1) and gpuDevice(2). But the proper multi-GPU way is to use a parallel pool with 2 workers. Get started with this blog post.
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