Perform MATLAB Computations on CUDA GPUs

Using MATLAB for GPU computing lets you accelerate your applications with GPUs more easily than by using C or Fortran. With the familiar MATLAB language you can take advantage of the CUDA GPU computing technology without having to learn the intricacies of GPU architectures or low-level GPU computing libraries.

You can use GPUs with MATLAB through Parallel Computing Toolbox, which supports:

  • CUDA-enabled NVIDIA GPUs with compute capability 2.0 or higher. For releases 14a and earlier, compute capability 1.3 is sufficient. In a future release, support for GPU devices of compute capability 2.x will be removed. At that time, a minimum compute capability of 3.0 will be required. 

  • GPU use directly from MATLAB
  • Multiple GPUs on the desktop and computer clusters using MATLAB workers in Parallel Computing Toolbox and MATLAB Distributed Computing Server

See also: parallel computing, MATLAB acceleration, GPUs for Signal Processing Algorithms, MATLAB GPU videos, research with MATLAB, deep learning

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