Thonk From First Principles
Horace He, Yanbo LiangML Systems from first principles. Aims to be better than a ChatGPT summary.
| Platform |  | Pricing | Freemium | Publishes | Monthly |
|---|---|---|---|---|---|
| Issues | 5 | Subscribers | Read | thonking.ai |
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FlexAttention: The Flexibility of PyTorch with the Performance of FlashAttention [external]
I have a blog post up on the PyTorch blog (as part of my day job) on FlexAttention: https://pytorch.org/blog/flexattention/ (work done with Driss Guessous, Yanbo Liang, and Joy Dong). And here’s a tweet thread.
Strangely, Matrix Multiplications on GPUs Run Faster When Given "Predictable" Data! [short]
It’s 2022. I check out this cool new project, CUTLASS, with very fast matmuls. I take a large matmul, 8192 x 8192 x 8192, and benchmark it in PyTorch, which calls CuBLAS.
What Shapes Do Matrix Multiplications Like? [medium]
A while back, Karpathy tweeted that increasing the size of his matmul made it run faster. Surprisingly, it’s not just relatively faster, it takes less absolute time. In other words, despite doing more work, it is executing in less time.
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