GPU support in Mathematica, Maple, MATLAB and Mathcad Prime

May 6th, 2011 | Categories: CUDA, GPU, Maple, math software, mathcad, mathematica, matlab, OpenCL, parallel programming | Tags:

Updated January 4th 2011

It is becoming increasingly common for programmers to make use of GPUs (Graphical Processing Units) to speed up their programs substantially.  There are three major low-level programming libraries that allow you to do this in languages such as C; namely CUDA, OpenCL and Microsoft DirectCompute.  Of these three, CUDA is the most developed but it only works on Nvidia graphics cards.

I am often asked if the major commercial math packages support GPU computing and I find myself writing the same summary email over and over again.  So, here is a very brief breakdown of what is currently on offer.  I plan to expand the information contained in this page over time so if you have any information about GPU computing in these packages then let me know.


Core MATLAB contains no support for GPU computing but several organizations (including The Mathworks themselves) have produced add-on toolboxes that add such support:

  • Jacket – This is a product from a company called AccelerEyes and is possibly the most advanced and well developed GPU solution for MATLAB currently available.  As of version 2.0 it supports both OpenCL and CUDA frameworks.
  • The Mathworks’ Parallel Computing Toolbox (PCT) – If you want to do your MATLAB GPU computing the officially supported way then this is the product you need.  As a bonus, it also allows you to make better use of the multicore processor that almost certainly resides in your machine.  Like many of the offerings on this page, only the CUDA framework is supported so you are out of luck if you don’t have an NVidia graphics card.  Even if you do have an NVidia graphics card then you still might be out of luck since the PCT only supports cards that have compute level 1.3 or above (i.e. double precision only).
  • CULA is a set of GPU-accelerated linear algebra libraries utilizing the NVIDIA CUDA parallel computing architecture and it has a MATLAB interface.
  • GPUmat – This product is completely free but is less developed than the commercial offerings above.  Again. it is CUDA only
  • OpenCL toolbox – The only OpenCL solution for MATLAB I could find.  It is free but development seems to have stalled.


Mathematica 8 has support for both CUDA and OpenCL built in so no need for any add-ons.  Furthermore, it supports both single and double precision GPUs so you can experiment with GPU computing on older, cheaper cards.


Maple has had some CUDA-only GPU support since version 14.  On the face of it, the CUDA package only appears to contain one accelerated function–Matrix-Matrix multiplication– but when you load this function it accelerates many functions that use matrix-matrix multiply internally.  I’ve never found a definitive list of such functions though.


Mathcad 15 and Mathcad Prime have no support for GPU enhanced computing.

  1. MySchizoBuddy
    May 6th, 2011 at 18:33
    Reply | Quote | #1

    CULA has matlab integration as well

  2. MySchizoBuddy
    May 6th, 2011 at 18:36
    Reply | Quote | #2

    Macs no longer come with Nvidia cards. So macs are left with only OpenCL.

  3. MySchizoBuddy
    May 6th, 2011 at 18:47
    Reply | Quote | #3

    Sorry for 3 posts.
    Scilab 6 has planned support for CUDA via their HPC project. Although 3 third party addons already add CUDA and OpenCL support to Scilab.

  4. May 10th, 2011 at 10:01
    Reply | Quote | #4

    @MySchizoBuddy – no need to be sorry – you’ve posted some great info.

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