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srush
GPU-Puzzles
Jupyter Notebook2022–2026
srush / GPU-Puzzles

GPU-Puzzles

Solve puzzles. Learn CUDA.

18Distinct people
20Mentions
0Explicit recommenders
12.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Solve puzzles. Learn CUDA.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year20 dated mentions

Observed mentions: 2022-07-12 16:56:57 UTC to 2026-06-19 23:13:01 UTC.

02462022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 4 mentions; 4 submissions, 0 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 5 mentions; 2 submissions, 3 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 6 mentions; 2 submissions, 4 comments20242025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC440
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC523
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC624
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC404
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC110

What Hacker News says

20 sources
Oh hey, I wrote this. Been a long time. I had the lucky of break of working in machine translation / parsing when the most important invention of the century happened in my niche field. I'm pretty interested in the intersection of code / ML. If that's your thing here are some other writing you might be interested in. * Thinking about cuda: http://github.com/srush/gpu-puzzles * Tensors considered harmful: https://nlp.seas.harvard.edu/NamedTensor * Differentiating SVG: https://srush.github.io/DiffRast/ * Annotated S4: https://srush.github.io/annotated-s4/ Recently moved back to industry, so haven't had a chance to write in a while.
In The Annotated Transformer (2022)
If you're looking for a high level introduction to GPU development on Apple silicon I would recommend learning Metal. It's Apple's GPU acceleration language similar to CUDA for Nvidia hardware. I ported a set of puzzles for CUDA called GPU-Puzzles (a collection of exercises designed to teach GPU programming fundamentals)[1] to Metal [2]. I think it's a very accessible introduction to Metal and writing GPU kernels. [1] https://github.com/srush/GPU-Puzzles [2] https://github.com/abeleinin/Metal-Puzzles
In Ask HN: Resources for general purpose GPU development on Apple's M* chips?
Hello HN Community, I'm excited to share a project that's been brewing for a while now, aimed at GPU enthusiasts and developers alike. Say hello to GPU-Puzzles, an open-source repository that's set to revolutionize how we approach GPU programming and optimization. Why GPUs? In a world where tech giants like Google, Apple, and Facebook are pushing the boundaries of what's possible with AI, machine learning, and high-performance computing, the GPU has become the unsung hero. It's the powerhouse behind the scenes, and GPU-Puzzles is here to help you harness its full potential. What's inside? You'll find a curated collection of puzzles, challenges, and solutions that are designed to test and expand your understanding of GPU architecture and programming. Whether you're a seasoned developer or just starting out, there's something for everyone.
Read the rest
Why should you care? With the rise of GPU-accelerated computing, the demand for skilled professionals is higher than ever. By working through the puzzles in GPU-Puzzles, you'll not only sharpen your skills but also contribute to the growing community of GPU experts. So, if you're ready to dive into the world of GPU programming, head over to https://github.com/srush/GPU-Puzzles and let the learning begin! Looking forward to your thoughts and contributions. Let's push the limits together!
In "Unlock GPU Power: GPU-Puzzles, Your GPU Innovation Hub"
Hey, I made these. They're pretty fun. Sometimes people tell me they use them for ML interviews, but they're kind of hard. The motivation was primarily teaching point-free, array programming. I don't think it is a great style, but it is fun as a brain teaser. If you enjoy this type of thing, I made a bunch more. They're all kind of ML + PL in style. - https://github.com/srush/gpu-puzzles - https://github.com/srush/tensor-puzzles - https://github.com/srush/autodiff-puzzles - https://github.com/srush/transformer-puzzles - https://github.com/srush/LLM-Training-Puzzles - https://github.com/srush/triton-puzzles All the graphics for these are made in Chalk which is a python port of Haskell's Diagrams library to https://github.com/chalk-diagrams/chalk . Honestly I mostly make the puzzles as an excuse to hack on the graphics library which I find
Read the rest
pretty interesting.
In Tensor Puzzles

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