GPU CUDA y programación MEX
Si ejecutar las funciones MATLAB® en la GPU no acelera lo suficiente su código, o si necesita usar funciones avanzadas de la GPU CUDA, puede escribir su propio código CUDA y ejecutarlo en MATLAB generando un archivo MEX ejecutable usando mexcuda o un kernel ejecutable. usando parallel.gpu.CUDAKernel .
Generalmente, usar archivos MEX es más flexible que usar objetos CUDAKernel. Para obtener más información, consulte Run MEX Functions Containing CUDA Code.
Funciones
Temas
- Run MEX Functions Containing CUDA Code
All MEX files, including those containing CUDA code, have a single entry point known as
mexFunction. - Run CUDA or PTX Code on GPU
This page explains how to create an executable kernel from a CUDA C++ source file (CU) file and run that kernel on a GPU in MATLAB.
Ejemplos destacados
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 Run MEX Functions Containing CUDA Code.
Illustrating Three Approaches to GPU Computing: The Mandelbrot Set
Adapt your MATLAB® code to compute the Mandelbrot Set using a GPU.
