GPU CUDA and MEX Programming

Further accelerate your code using advanced GPU CUDA and MEX programming

Functions

Key Functions

`mexcuda`	Compile MEX-function for GPU computation
`parallel.gpu.CUDAKernel`	Create GPU CUDA kernel object from PTX and CU code
`feval`	Evaluate kernel on GPU
`setConstantMemory`	Set some constant memory on GPU

C Functions

`mxGPUCopyFromMxArray`	Copy mxArray to mxGPUArray
`mxGPUCopyGPUArray`	Duplicate (deep copy) mxGPUArray object
`mxGPUCopyImag`	Copy imaginary part of mxGPUArray
`mxGPUCopyReal`	Copy real part of mxGPUArray
`mxGPUCreateComplexGPUArray`	Create complex GPU array from two real gpuArrays
`mxGPUCreateFromMxArray`	Create read-only mxGPUArray object from input mxArray
`mxGPUCreateGPUArray`	Create mxGPUArray object, allocating memory on GPU
`mxGPUCreateMxArrayOnCPU`	Create mxArray for returning CPU data to MATLAB with data from GPU
`mxGPUCreateMxArrayOnGPU`	Create mxArray for returning GPU data to MATLAB
`mxGPUDestroyGPUArray`	Delete mxGPUArray object
`mxGPUGetClassID`	mxClassID associated with data on GPU
`mxGPUGetComplexity`	Complexity of data on GPU
`mxGPUGetData`	Raw pointer to underlying data
`mxGPUGetDataReadOnly`	Read-only raw pointer to underlying data
`mxGPUGetDimensions`	mxGPUArray dimensions
`mxGPUGetNumberOfDimensions`	Size of dimension array for mxGPUArray
`mxGPUGetNumberOfElements`	Number of elements on GPU for array
`mxGPUIsSame`	Determine if two mxGPUArrays refer to same GPU data
`mxGPUIsSparse`	Determine if mxGPUArray contains sparse GPU data
`mxGPUIsValidGPUData`	Determine if mxArray is pointer to valid GPU data
`mxGPUSetDimensions`	Modify number of dimensions and size of each dimension
`mxIsGPUArray`	Determine if mxArray contains GPU data
`mxInitGPU`	Initialize MATLAB GPU library on currently selected device

Classes

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Key Classes

CUDAKernel Kernel executable on GPU

C Classes

mxGPUArray Type for MATLAB gpuArray

Topics

Run CUDA or PTX Code on GPU

This topic explains how to create an executable kernel from CU or PTX (parallel thread execution) files, and run that kernel on a GPU from MATLAB^®.

Run MEX-Functions Containing CUDA Code

As with any MEX-files, those containing CUDA^® code have a single entry point, known as mexFunction.

Featured Examples

Accessing Advanced CUDA Features Using MEX

Demonstrates how advanced features of the GPU can be accessed using MEX files. It builds on the example Stencil Operations on a GPU. The previous example uses Conway's "Game of Life" to demonstrate how stencil operations can be performed using MATLAB® code that runs on a GPU. The present example demonstrates how you can further improve the performance of stencil operations using two advanced features of the GPU: shared memory and texture memory. You do this by writing your own CUDA code in a MEX file and calling the MEX file from MATLAB. You can find an introduction to the use of the GPU in MEX files in Run MEX-Functions Containing CUDA Code.

Open Script

Parallel Computing Toolbox Documentation

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