GPU Code Generation
After you develop your application using Wavelet Toolbox™, you can generate optimized CUDA code for NVIDIA® GPUs from MATLAB code. The code can be integrated into your project as source code, static libraries, or dynamic libraries, and can be used for prototyping on GPUs. You can use the generated CUDA within MATLAB to accelerate computationally intensive portions of your MATLAB code in machine learning, deep learning, or other applications. You must have MATLAB Coder™ and GPU Coder™ to generate CUDA code.
For a list of functions that support GPU code generation, see Function List (GPU Code Generation).
Apps
| GPU Coder | Generate CUDA code from MATLAB code |
Functions
codegen | Generate C/C++ code from MATLAB code |
coder.gpuConfig | Configuration parameters for CUDA code generation from MATLAB code by using GPU Coder |
Topics
- Generate Code by Using the GPU Coder App (GPU Coder)
Generate CUDA code from MATLAB code by using the GPU Coder app.
- Getting Started with the MATLAB Coder Support Package for NVIDIA Jetson and NVIDIA DRIVE Platforms (MATLAB Coder)
This example shows how to use the MATLAB® Coder™ Support Package for NVIDIA Jetson™ and NVIDIA DRIVE® Platforms with embedded boards from NVIDIA®.
Featured Examples
CUDA Code from CWT
Learn how to generate CUDA Code for the CWT.
Deploy Signal Classifier on NVIDIA Jetson Using Wavelet Analysis and Deep Learning
Generate and deploy a CUDA executable to classify electrocardiogram signals using wavelet-derived features.
