CUDA Programming with Mathematica
Mathematica is a sophisticated development environment that combines a flexible programming language with a wide range of symbolic and numeric computational capabilities, production of high-quality visualizations, built-in application packages, and a range of immediate deployment options. With access to thousands of datasets and the ability to load external dynamic libraries and automatically generate C code, Mathematica is the most intuitive build-to-deploy environment in the market.
Learn more about GPU computing with Wolfram Mathematica [here] |
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Mathematica’s CUDALink: Integrated GPU ProgrammingMathematica provides GPU programming support via the built-in CUDALink package, which gives you GPU accelerated linear algebra, discrete Fourier transform, and image processing algorithms. You can also write your own CUDALink modules with minimal effort.The CUDALink package included within Mathematica at no additional cost offers:
Learn more about High Performance Computing with Wolfram Mathematica. |
Additional Resources
- Mathematica GPU Computing Guide [here]
- Mathematica CUDALink Tutorial [here]
- Mathematica OpenCLLink Tutorial [here]
- CUDA Programming within Mathematica – Wolfram whitepaper [here]
Example: Performing Canny edge detection
Example: Simulating a random walk

Recommended Professional Products
To utilize Mathematica's CUDALink, the following is required:
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The powerful GPU computing capabilities in Mathematica were developed on Tesla and Quadro GPU computing products and require the use of recent CUDA-capable NVIDIA GPUs.
Tesla and Quadro GPU computing products are designed to deliver the highest computational performance with the most reliable numerical accuracy, and are available and supported by the world’s leading professional system manufacturers. |
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NVIDIA Tesla and Quadro products are available from all major professional workstation OEMs. Only Tesla GPU computing products are designed and qualified for compute cluster deployment.
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