CUDA: Difference between revisions
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[http://developer.nvidia.com/what-cuda CUDA]is NVIDIA’s parallel computing architecture. It enables dramatic increases in computing performance by harnessing the power of the GPU. | [http://developer.nvidia.com/what-cuda 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. | 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. | ||
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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
The following Modules file should be loaded for this package:
module load cuda/cuda-4