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SOLUTIONS
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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.
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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 ▪ ...





