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 ▪ ...