Lykke Kempfne asked . 2022-04-01

Nvidia NVLink in MATALB using multiple Geforce 2080 ti cards

The NVLink yields a high bidirectional bandwidth between the cards (the Geforce 2080 ti offers 100 GB/, while the GeForce RTX 2080 offers 50GB/s). When fully utilized, the NVLink will minimize inter-GPU traffic over the PCI Express interface and also allows the memory on each card to behave more as a single, shared resource. This opens up the possibility for new multi-GPU modes for scientific analysis and big dataworkloads as well.

Will Matlab take advantage of the nvlinks ability to share resources between cards in future releases (R2019a/R2019b)?

AI, Data Science, and Statistics , Deep Learning Toolbox , Deep Learning in Parallel and in the

Expert Answer

John Williams answered . 2024-12-21 01:48:24

I understand that you want to use Nvidia NVLink with MATLAB to leverage multiple Nvidia Geforce 2080 ti graphic cards.

Currently, there is no straightforward way to utilize the high bidirectional bandwidth to distribute the computations across the available GPUs. This would be possible with the introduction of distributed GPU arrays which can use all GPUs and gather the results back automatically. Distributed GPU arrays are currently not supported in MATLAB.

Our development teams are aware of this and are currently considering "distributed GPU Arrays" for future releases of MATLAB.

Currently, there are no commands to enable NVLink in MDCS. As a workaround to leverage NVlink, you can use "gop" function as in example given below that does the computation in each gpu and get the result back :

>> gop(@plus, gpuArray(X), 'gpuArray');

Open a parpool and issue local and/or communicating instructions via spmd that will allow to do distributed computation between the GPUs.

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