In this session, we will demonstrate simple ways to improve and optimize your code that can boost execution speed.  We will also address common pitfalls in writing MATLAB code, explore the use of the MATLAB Profiler to find bottlenecks, and introduce programming constructs to solve computationally and data-intensive problems on multicore computers, clusters and GPUs.  

Specifically, we will show:

• Leveraging the power of vector and matrix operations in MATLAB
• Identifying and addressing bottlenecks in your code
• Converting MATLAB code to C/C++ using MATLAB Coder
• Utilizing additional processing power available in multicore machines, clusters, and grids

Prior to R2019a, MATLAB Parallel Server was called MATLAB Distributed Computing Server.