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CUDA Books

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Re: CUDA Books

#31

Post by saagarjha »

dahart wrote: post #12
juvoly wrote: post #9

Increasingly (for instance ADSP podcast [1]) those in nvidia's inner circle are advocating against writing your own CUDA kernels. (Unless that's your full time job at nvidia, that is). [1] https://adspthepodcast.com/2024/08/30/Episode-197.html

It’s not about whether you work at Nvidia. Avoid writing CUDA kernels if there are higher level libraries that do what you need. Do write CUDA kernels if you want to learn how, or if you need the low level control, or to micro-optimize. Being able to fuse kernels to avoid memory traffic or get better specialization is also a reason to reach for raw CUDA. Just consider what’s the right tool for the job…

I don't think writing CUDA is a good way to do this tbh

Re: CUDA Books

#32

Post by saagarjha »

Probably worth noting that writing performant kernels for modern Nvidia hardware looks almost nothing like what the books from 2012 are going to teach you. You can read them for fun if you'd like but they're basically irrelevant.

Re: CUDA Books

#33

Post by iamcreasy »

somethingsome wrote: post #14

Having read or at least skimmed most of those books, I think the best intro is 'CUDA Programming: A Developer's Guide to Parallel Computing with GPUs' 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 archi…

Interesting, thanks for sharing.

What makes CUDA Programming: A Developer's Guide to Parallel Computing with GPUs better among its peers?

Re: CUDA Books

#36

Post by boomzilla »

somethingsome wrote: post #14

Having read or at least skimmed most of those books, I think the best intro is 'CUDA Programming: A Developer's Guide to Parallel Computing with GPUs' 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 archi…

How about this guide:

https://docs.nvidia.com/cuda/cuda-programming-guide/pdf/cuda...

Re: CUDA Books

#37

Post by signa11 »

phoronixrly wrote: post #2

In an age when your company mandates you to raise your productivity right now with hundreds of percentage points using LLMs, how do you find an excuse to sit down and read a book?

not on company time ?

Re: CUDA Books

#38

Post by tirutiru »

dahart wrote: post #13

Regarding the section on Python and high-level CUDA, anyone interested should maybe first take a peek at Warp, which I’m guessing is too new to have a book yet. Warp lets you write CUDA kernels directly in Python, and it’s a breeze to get started. https://github.com/nvidia/warp

It's a bit confusing now with Numba Cuda also being officially maintained by Nvidia. Also Cuda Python, which looks older.

Which of these - warp, numba, cp, is the best bet for a beginner?

https://nvidia.github.io/numba-cuda/

https://developer.nvidia.com/cuda/python

Re: CUDA Books

#39

Post by KnuthIsGod »

somethingsome wrote: post #14

Having read or at least skimmed most of those books, I think the best intro is 'CUDA Programming: A Developer's Guide to Parallel Computing with GPUs' 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 archi…

Thank you, that is very useful advice !

Re: CUDA Books

#40

Post by pjmlp »

drnick1 wrote: post #20
juvoly wrote: post #9

Increasingly (for instance ADSP podcast [1]) those in nvidia's inner circle are advocating against writing your own CUDA kernels. (Unless that's your full time job at nvidia, that is). [1] https://adspthepodcast.com/2024/08/30/Episode-197.html

That advice seems like nonsense. It's like saying avoid C because you can use Python, or avoid writing a graphics engine because you can license Unreal.

Not at all, the advice is like use SDL or Raylib instead of writing your framebuffer blitter in inline Assembly to call from C.
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