- Shows how to accelerate MATLAB codes through the GPU for parallel processing, with minimal hardware knowledge
- Explains the related background on hardware, architecture and programming for ease of use
- Simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects
Matlab is a widely used simulation tool for rapid prototyping and algorithm development. In many laboratories and research institutions, there is growing interest in running Matlab codes faster for computationally heavy projects and leveraging the distributed parallelism of graphics processing units (GPUs). However, Matlab users come from various backgrounds and do not necessarily have strong programming experience. Without guidance, those users may find their work delayed due to the learning curve of GPUs and the CUDA library. This book will target readers who have experience with Matlab coding but don’t have enough depth in either C coding or computer architecture. As a primer, the book starts with basics, setting up Matlab for CUDA (in Windows and Mac OSX), profiling, and then guiding users through advanced topics such as OpenACC, third-party CUDA libraries and debugging. It will also provide many practical ways to modify Matlab codes to better utilize the computational power of GPUs. The authors have extensive experience developing algorithms using Matlab, C++ and GPUs for huge datasets in industrial and research fields and integrating them into commercial software products. They have published more than a dozen papers on these subjects.
Graduate students and researchers in a variety of fields, who need huge data processing without losing the many benefits of Matlab.