Applications
Explore examples for accelerating simulations, solvers, statistical models, signal
processing, and image processing
Parallel Computing Toolbox™ lets you solve compute- and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—enable you to scale MATLAB® applications without CUDA® or MPI programming.
Explore these examples to discover how parallel computing can reduce the time it takes to get results.
Categories
- Parallel Computing in Simulink
Accelerate Simulink® simulations with parallel computing
- Optimization
Accelerate solving optimization problems with parallel computing
- AI and Statistics
Accelerate statistics, machine learning, and deep learning applications with parallel computing
- Signal Processing, Audio, and Wireless
Accelerate signal processing, audio processing, wireless communications, and radar processing applications
- Image Processing and Computer Vision
Accelerate image processing, computer vision, and medical imaging applications with parallel computing
- Predictive Maintenance
Accelerate predictive maintenance applications with parallel computing