GPU memory fragmentation

I have been running GPU code on 480 and 580 GTX cards in R2011b for a while and I keep hitting memory fragmentation problems. Either from straigtforward gpuArray routines (conv2, boolean comparisons, repmat multiplication, etc) of from simple CUDA kernels that should not require much memory at all.

I got in the habit of clearing loop variables defined on the GPU before every iteration, as they seem to creep up in the memory footprint without changing the actual array size or type, but aside from that I don't know any good way to avoid running into the fragmentation thing. Any tips or secret defrag commands?

Answer 1

[Jason Ross]

In 2012a, a "reset" command has been added:

Description

reset(gpudev) resets the GPU device and clears its memory of GPUArray and CUDAKernel data. The GPU device identified by gpudev remains the selected device, but all GPUArray and CUDAKernel objects in MATLAB representing data on that device are invalid.

http://www.mathworks.com/help/toolbox/distcomp/reset.html

Answer 2

[Image Analyst]

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