MATLAB Parallel programming on GPUs, Cores and CPUs

This course helps students, researchers, and anyone else who works with MATLAB cut down on the time it takes to run a program.

They all have multi-core CPUs and graphics cards now, and laptops have them as well. But not all people use the to run or run programs at the same time.

Its goal is to fill this gap. Is to show you how to use all the resources on your computer and also how to keep an eye on them.

The course is broken up into many parts:

1. The first is about the hardware of the CPUs, cores, and GPUs.
2. The second part explains two things. The multi-threading and the many people who work. The first is a built-in way to run some functions at the same time on many cores, but we can’t control how many cores there are or how the functions run. Also, I gave some examples and measured how well they worked to show the difference between the two concepts.
3. The third section is called the GPU section, and it is the last one. There, I told you how to run any function on the GPUs to make the most of the hundred or thousands of cores that the GPUs have. It’s important to use certain notations to get the best results, and I’ve shown you how these notations work with examples so you can see what they look like.
4. How to train any neural network on a GPU or multiple cores in this section: You’ll learn how to do this with any neural network in this section. It also tells you how to run a training process in the background so that you can use MATLAB while it is going on.