CUDA Books(github.com) |
CUDA Books(github.com) |
Massively Parallel Processors: A Hands-on Approach is not really good in my opinion, many small mistakes and confusing sentences (even when you know cuda).
CUDA by Example: An Introduction to General-Purpose GPU Programming is too simple and abstract too much the architecture.
Next year I'm planning to start writing a cuda book that starts by engineering the hardware, and goes up to the optimization part on that harware (which is basically a nvidia card) including all the main algorithms (except for graphs).
I'm already teaching the course in this way at uni, and it is quite successful among students.
https://docs.nvidia.com/cuda/cuda-programming-guide/pdf/cuda...
What makes CUDA Programming: A Developer's Guide to Parallel Computing with GPUs better among its peers?
I always appreciate book lists like this one, but having a small targeted list is more practical for those of us with limited reading time.
So tl;dr, you have at least one person who would pay for a better book :-)
Understand everything he talks about and you understand CUDA.
In this day and age when programming is so accessible, why not have a more tempting pitch than just book titles categorized by difficulty.
I started learning about GPU and CUDA from this book recently, and I agree the writing is confusing, and code examples have errors. However, it is still a nice reference about many types of algorithms for heterogeneous memory devices, it helped me understand better some patterns for CPUs.