GPU computations slowing down
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Within a loop, my code carries out some iterative solving procedure on the GPU. With every loop iteration, the time taken by the solving procedure increases. There doesn't seem to be a memory leak: gpuDevice consistently reports approximately the following:
TotalMemory: 1.2885e+10
AvailableMemory: 5.6773e+09
However, when I pause the loop for a while by means of a debug stop, after relaunching again, computations are up to speed again, after which they start slowing down again...
I'm running matlab2016b on Windows 10, using a Nvidia Titan X (Pascal) GPU. Any suggestions for this problem?
3 件のコメント
Jan
2017 年 1 月 5 日
Without seeing the code or knowing any details, it is hard to guess, what's going on. Did you control the temperature of the graphics board?
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Peter
2017 年 1 月 6 日
1 件のコメント
Joss Knight
2017 年 1 月 8 日
Most people who report issues like this are simply seeing an issue of asynchronous execution. They see fast times until the kernel execution queue is full, and then they start seeing the actual complete computation times.
To avoid this try using wait(gpuDevice) to add synchronisation points to your code.
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