GPU Coder™ generates optimized CUDA® code from MATLAB® code for deep learning, embedded vision, and autonomous systems. The generated code calls optimized NVIDIA CUDA libraries, including cuDNN, cuSolver, and cuBLAS. It can be integrated into your project as source code, static libraries, or dynamic libraries, and can be used for prototyping on GPUs such as the NVIDIA Tesla® and NVIDIA Tegra®. You can use the generated CUDA within MATLAB to accelerate computationally intensive portions of your MATLAB code. GPU Coder lets you incorporate legacy CUDA code into your MATLAB algorithms and the generated code.
When used with Embedded Coder®, GPU Coder lets you verify the numerical behavior of the generated code via software-in-the-loop (SIL) testing.
Generate code from a broad range of MATLAB language features and toolboxes used for developing components of larger systems.Learn more
Call MEX functions to test and verify the compiled code in MATLAB and accelerate the execution.Learn more
Run the generated CUDA on NVIDIA GPUs such as Tesla and Tegra.Learn more
Discover more about GPU Coder by exploring these resources.
Explore documentation for GPU Coder functions and features, including release notes and examples.
Browse the list of available GPU Coder functions.
View system requirements for the latest release of GPU Coder.
View articles that demonstrate technical advantages of using GPU Coder.
Use GPU Coder to solve scientific and engineering challenges: