GPU Computing

With the Wolfram Language, the enormous parallel processing power of Graphical Processing Units (GPUs) can be used from an integrated built-in interface. Incorporating GPU technology into the Wolfram Language allows high-performance solutions to be developed in many areas such as financial simulation, image processing, and modeling. GPU program creation and deployment is fully integrated with the Wolfram Language's high-level development tools and this gives a productivity boost to move from prototype to large-scale solution.

GPU Computing Using CUDALink »

CUDAInformation lists all CUDA device information

CUDAImageConvolve convolves images with specified kernel

CUDAFunctionLoad loads a user-defined function to run on a GPU using CUDA

CUDAErosion  ▪  CUDADilation  ▪  CUDAFourier  ▪  CUDADot  ▪  ...

CUDAMemoryLoad  ▪  CUDAMemoryAllocate  ▪  SymbolicCUDAFunction  ▪  ...

GPU Computing Using OpenCLLink »

OpenCLInformation lists all OpenCL device information

OpenCLFunctionLoad loads a user-defined function to run on a GPU using OpenCL

OpenCLMemoryLoad  ▪  OpenCLMemoryAllocate  ▪  SymbolicOpenCLFunction  ▪  ...

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