MATLAB® is a high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models in a variety of application areas such as image and video processing, signal processing and communications, computational finance, machine learning, and computational biology.
MATLAB supports CUDA kernel development by providing a language and development environment for prototyping algorithms and incrementally developing and testing CUDA kernels.
Technical article: Prototyping Algorithms and testing CUDA Kernels in MATLAB
Webinar: MATLAB for CUDA Programmers
Technical article: GPU Programming with MATLAB
MATLAB can be used to:
MATLAB reduces the amount of wrapper code required for evaluating and testing CUDA kernels compared with lower level languages such as C or Fortran.
Learn more about GPU Computing with MATLAB
Try GPU accelerated MATLAB yourself: MATLAB GPU Hands-On Tutorial
When it’s not required to deliver your final application in C or Fortran, you can save time by developing your application directly in MATLAB and leveraging the built-in GPU-enabled functions in MATLAB and application specific toolboxes such as Image Processing Toolbox, Signal Processing Toolbox, and Communications System Toolbox. Parallel Computing Toolbox is required to call GPU-enabled functions or integrate CUDA kernels in MATLAB. You also need a CUDA-enabled NVIDIA GPU with compute capability 1.3 or later.