Hands-On GPU Programming with Python and CUDA

Kernels

As in the last chapter, we'll be learning how to write CUDA kernel functions as inline CUDA C in our Python code and launch them onto our GPU using PyCUDA. In the last chapter, we used templates provided by PyCUDA to write kernels that fall into particular design patterns; in contrast, we'll now see how to write our own kernels from the ground up, so that we can write a versatile variety of kernels that may not fall into any particular design pattern covered by PyCUDA, and so that we may get a more fine-tuned control over our kernels. Of course, these gains will come at the expense of greater complexity in programming; we'll especially have to get an understanding of threads, blocks, and grids and their role in kernels, as well as ...