Can I use Parallel processing toolbox directly on GPU (Geforce GT 520MX). How.
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I would like to use image clustering with GPU. Please provide me an example on it. OpenCl is a platform but its a platform not a tool. Please clearify if any other method is availbe directly to utilize GPU.
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Jason Ross
am 26 Sep. 2012
Bearbeitet: Walter Roberson
am 27 Sep. 2012
To use the GPU with MATLAB, only CUDA is supported and you need the Parallel Computing toolbox.
You must also have a GPU with compute capability 1.3 or higher ( http://developer.nvidia.com/cuda/cuda-gpus). It looks like your card has a compute capability of 2.1 so you should be OK.
I would offer a word of caution regarding the performance of the GPU -- according to the specs for the GPU ( http://www.geforce.com/hardware/notebook-gpus/geforce-gt-520mx/specifications), it has only 48 CUDA cores, and the amount of memory is not specified. The performance of this card isn't likely to give much of a performance boost -- as a comparison the GTX 680 has 1536 cores and 2 GB RAM on the card, and the Tesla C2075 has 448 cores / 6 GB RAM.
For examples, there are a number here: http://www.mathworks.com/help/distcomp/examples/index.html#gpu
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Jason Ross
am 28 Sep. 2012
To use MATLAB with the GPU, install the proper driver from nVidia's website -- make sure you get the CUDA enabled driver. MATLAB will find the device and you can start using it.
There have been a number of new GPU-related features added each release since 2010b, so I would recommend you look into getting the most recent release that you can. The link I provided has the relevant examples in it.
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