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GPU Puzzles

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Re: GPU Puzzles

#11

Post by xandrius »

fifilura wrote: post #5
xandrius wrote: post #2

Looks nice and fun but the "see-through" font for the titles in the screenshots gives me some deep and primordial unease, not sure why.

https://en.wikipedia.org/wiki/Astigmatism Maybe?

This: https://github.com/srush/GPU-Puzzles/raw/main/GPU_puzzlers_f...

Re: GPU Puzzles

#12

Post by nextos »

srush wrote: post #4

I made these a couple of years ago as a teaching exercise for https://minitorch.github.io/ . At the time the resources for doing anything on GPUs were pretty sparse and the NVidia docs were quite challenging. These days there are great resources for going deep on this topic. The CUDA-mode org is particularly great, both their video series and PMPP reading groups.

Slightly offtopic, but any chance you could update or re-upload code for your https://github.com/harvardnlp/DeepLatentNLP tutorial? I found the NLP latent variable models discussed there really interesting, and notebooks were excellent. However, these seem gone and the only thing left are slides?

Alternatively, any other places that discuss the same topics, including some code? I could only find equivalent discussions with code in Pyro docs and Kevin Murphy's book, volume 2. But these are more sparse as they also cover many other topics.

Re: GPU Puzzles

#13

Post by throwaway314155 »

Either puzzle 4 has a bug in it or I'm losing my mind. (Possible answer to solution below, so don't read if you want to go in fresh)

    # FILL ME IN (roughly 2 lines)
    if local_i
Results in a failed assertion:

     AssertionError: Wrong number of indices
But the test cell beneath it will still pass?

Re: GPU Puzzles

#16

Post by srush »

nextos wrote: post #12
srush wrote: post #4

I made these a couple of years ago as a teaching exercise for https://minitorch.github.io/ . At the time the resources for doing anything on GPUs were pretty sparse and the NVidia docs were quite challenging. These days there are great resources for going deep on this topic. The CUDA-mode org is particularly great, both their video series and PMPP reading groups.

Slightly offtopic, but any chance you could update or re-upload code for your https://github.com/harvardnlp/DeepLatentNLP tutorial? I found the NLP latent variable models discussed there really interesting, and notebooks were excellent. However, these seem gone and the only thing left are slides? Alternatively, any other places that discuss the same topics, including some code? I could only find equivalent discussion…

I'll take a look. Yeah Pyro is the best thing to do here. But it would be nice to revisit some of these implementationz

Re: GPU Puzzles

#18

Post by lins1909 »

srush wrote: post #4

I made these a couple of years ago as a teaching exercise for https://minitorch.github.io/ . At the time the resources for doing anything on GPUs were pretty sparse and the NVidia docs were quite challenging. These days there are great resources for going deep on this topic. The CUDA-mode org is particularly great, both their video series and PMPP reading groups.

Thanks Sasha - this looks like a great resource.Just to be clear, would you recommend going through other newer resources than this instead?

Not sure if your comment is to discourage someone from going through this.

Re: GPU Puzzles

#19

Post by imjonse »

throwaway314155 wrote: post #13

Either puzzle 4 has a bug in it or I'm losing my mind. (Possible answer to solution below, so don't read if you want to go in fresh) # FILL ME IN (roughly 2 lines) if local_i Results in a failed assertion: AssertionError: Wrong number of indices But the test cell beneath it will still pass?

maybe try out[local_i, local_j] ?

Re: GPU Puzzles

#20

Post by srush »

lins1909 wrote: post #18
srush wrote: post #4

I made these a couple of years ago as a teaching exercise for https://minitorch.github.io/ . At the time the resources for doing anything on GPUs were pretty sparse and the NVidia docs were quite challenging. These days there are great resources for going deep on this topic. The CUDA-mode org is particularly great, both their video series and PMPP reading groups.

Thanks Sasha - this looks like a great resource.Just to be clear, would you recommend going through other newer resources than this instead? Not sure if your comment is to discourage someone from going through this.

These still hold up, and I think they're a great first step. But they no longer get you to the goal line. Think about it more as conceptual practice, before you enter the jungle.
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