GPU CUDA 및 MEX 프로그래밍

고급 GPU CUDA® 및 MEX 프로그래밍을 사용하여 코드 속도 더욱 향상

GPU에서 MATLAB® 함수를 실행해도 코드 속도가 충분히 빠르지 않은 경우나 고급 GPU CUDA 기능을 사용해야 하는 경우, CUDA 코드를 직접 작성하고 mexcuda를 사용해 실행 가능한 MEX 파일을 생성하거나 parallel.gpu.CUDAKernel을 사용해 실행 가능한 커널을 생성하여 MATLAB에서 해당 코드를 실행할 수 있습니다.

일반적으로 MEX 파일을 사용하는 것이 CUDAKernel 객체를 사용하는 것보다 유연합니다. 자세한 내용은 CUDA 코드가 포함된 MEX 함수 실행 항목을 참조하십시오.

함수

모두 확장

mexcudaGPU 연산을 위해 MEX 함수 또는 PTX 파일 컴파일
CUDAKernelGPU에서 실행 가능한 커널
fevalEvaluate kernel on GPU
setConstantMemorySet some constant memory on GPU
mxGPUArrayType for MATLAB gpuArray
mxGPUCopyFromMxArrayCopy mxArray to mxGPUArray
mxGPUCopyGPUArrayDuplicate (deep copy) mxGPUArray object
mxGPUCopyImag Copy imaginary part of mxGPUArray
mxGPUCopyReal Copy real part of mxGPUArray
mxGPUCreateComplexGPUArrayCreate complex GPU array from two real gpuArrays
mxGPUCreateFromMxArrayCreate read-only mxGPUArray object from input mxArray
mxGPUCreateGPUArrayCreate mxGPUArray object, allocating memory on GPU
mxGPUCreateMxArrayOnCPUCreate mxArray for returning CPU data to MATLAB with data from GPU
mxGPUCreateMxArrayOnGPUCreate mxArray for returning GPU data to MATLAB
mxGPUDestroyGPUArrayDelete mxGPUArray object
mxGPUGetClassIDmxClassID associated with data on GPU
mxGPUGetComplexityComplexity of data on GPU
mxGPUGetDataRaw pointer to underlying data
mxGPUGetDataReadOnlyRead-only raw pointer to underlying data
mxGPUGetDimensionsmxGPUArray dimensions
mxGPUGetNumberOfDimensionsSize of dimension array for mxGPUArray
mxGPUGetNumberOfElementsNumber of elements on GPU for array
mxGPUIsSameDetermine if two mxGPUArrays refer to same GPU data
mxGPUIsSparseDetermine if mxGPUArray contains sparse GPU data
mxGPUIsValidGPUDataDetermine if mxArray is pointer to valid GPU data
mxGPUSetDimensionsModify number of dimensions and size of each dimension
mxIsGPUArrayDetermine if mxArray contains GPU data
mxInitGPUInitialize MATLAB GPU library on currently selected device

도움말 항목

추천 예제

Accessing Advanced CUDA Features Using MEX

Accessing Advanced CUDA Features Using MEX

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 an advanced feature of the GPU: shared 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 CUDA 코드가 포함된 MEX 함수 실행.

Illustrating Three Approaches to GPU Computing: The Mandelbrot Set

Illustrating Three Approaches to GPU Computing: The Mandelbrot Set

Adapt your MATLAB® code to compute the Mandelbrot Set using a GPU.