In this chapter, we went over some of the options and paths for those that are interested in furthering their background in GPU programming, which is beyond the scope of this book. The first path we covered was expanding your background in pure CUDA and GPGPU programming—some of the things you can learn about that weren't covered in this book include programming systems with multiple GPUs and networked clusters. We also looked at some of the parallel programming languages/APIs besides CUDA, such as MPI and OpenCL. Next, we discussed some of the well-known APIs available to those who are interested in applying GPUs to rendering graphics, such as Vulkan and DirectX 12. We then looked at machine learning and went into some of the basic backgrounds that you should have as well as some of the major frameworks available for developing deep neural networks. Finally, we ended by taking a brief look at blockchain technology and GPU-based cryptocurrency mining.

As the author, I would like to say thank you to everyone who has pushed through this book and made it here, to the end. GPU programming is one of the trickiest subfields of programming that I have encountered, and I hope my text has helped you come to grips with the essentials. As the reader, you should now feel free to indulge in a slice of the richest, most calorie-laden slice of chocolate cake you can find—just know that you've earned it. (But only one slice!)