GPU Computing

 With Mathematica, the enormous parallel processing power of Graphical Processing Units (GPUs) can be used from an integrated built-in interface. Incorporating GPU technology into Mathematica 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 Mathematica's high-level development tools and this gives a productivity boost to move from prototype to large-scale solution.

ReferenceReference

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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