CUDA

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Attention: Research Computing Documentation has Moved
https://docs.rc.uab.edu/


Please use the new documentation url https://docs.rc.uab.edu/ for all Research Computing documentation needs.


As a result of this move, we have deprecated use of this wiki for documentation. We are providing read-only access to the content to facilitate migration of bookmarks and to serve as an historical record. All content updates should be made at the new documentation site. The original wiki will not receive further updates.

Thank you,

The Research Computing Team

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Compute Unified Device Architecture (CUDA)is NVIDIA’s parallel computing architecture. It enables dramatic increases in computing performance by harnessing the power of the GPU. CUDA is the computing engine in Nvidia graphics processing units (GPUs) that is accessible to software developers through variants of industry standard programming languages. Programmers use 'C for CUDA' (C with Nvidia extensions and certain restrictions), compiled through a PathScale Open64 C compiler, to code algorithms for execution on the GPU. CUDA architecture shares a range of computational interfaces with two competitors: the Khronos Group's OpenCL and Microsoft's DirectCompute

With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for CUDA, including image and video processing, computational biology and chemistry, fluid dynamics simulation, CT image reconstruction, seismic analysis, ray tracing, and much more.

Project website: http://developer.nvidia.com/what-cuda

Load SGE module

The following Modules file should be loaded for this package:

 module load cuda/cuda-4