By DE Editors
MathWorks has announced support for NVIDIA graphics processing units (GPUs) in MATLAB applications using Parallel Computing Toolbox or MATLAB Distributed Computing Server. This support enables engineers and scientists to increase the speed of many of their MATLAB computations without performing low-level programming.
Now more engineers can take advantage of NVIDIA’s CUDA-enabled GPUs, including the latest Tesla 20-series GPUs, based on the Fermi architecture, all from within MATLAB. Parallel Computing Toolbox users can access the NVIDIA CUDA library without having to learn CUDA programming or significantly modify their applications.
“MATLAB’s ease of use enables the engineering and scientific community to quickly adopt GPUs for technical computing,” says Silvina Grad-Freilich, manager of parallel-computing marketing at MathWorks. “MathWorks initial support for NVIDIA’s CUDA-enabled GPUs lets MATLAB users take advantage of GPUs to achieve significant speed-up of their applications. Parallel Computing Toolbox enables engineers and scientists in MATLAB to access all available computing resources available to them, from multicores and GPUs on local desktops to clusters and grids, with minimal programming effort.”
For more information, visit MathWorks.
Sources: Press materials received from the company and additional information gleaned from the company’s website.