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Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

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145•isitcontent•6h ago•15 comments

Show HN: I spent 4 years building a UI design tool with only the features I use

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250•vecti•8h ago•119 comments

Show HN: If you lose your memory, how to regain access to your computer?

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Show HN: R3forth, a ColorForth-inspired language with a tiny VM

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Show HN: Artifact Keeper – Open-Source Artifactory/Nexus Alternative in Rust

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Show HN: FastLog: 1.4 GB/s text file analyzer with AVX2 SIMD

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Show HN: Falcon's Eye (isometric NetHack) running in the browser via WebAssembly

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Show HN: A Kubernetes Operator to Validate Jupyter Notebooks in MLOps

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Show HN: A password system with no database, no sync, and nothing to breach

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Show HN: Hibana – An Affine MPST Runtime for Rust

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Show HN: Agent Arena – Test How Manipulation-Proof Your AI Agent Is

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45•joozio•15h ago•47 comments
Open in hackernews

Show HN: Sparse Matrix-Vector Multiplication that works at 30–90% sparsity

https://github.com/vlejd/macko_spmv
7•vlejd•2mo ago
To get benefits from sparsity, you usually need to have very sparse matrices, impose some structure on the sparsity pattern or have specialized hardware. None of it is the case if you want to rune pruned LLMs on consumer devices. I wanted to see how far can you push it on a GPU and ended up with this. Blog: https://www.grizzlytech.dev/blog/macko-spmv Paper: https://arxiv.org/abs/2511.13061 Code (example with torch): https://github.com/vlejd/macko_spmv

Comments

jjgreen•2mo ago
Interesting approach -- thanks
telmop•2mo ago
Cool method. Pre deep learning there was plenty of interesting research on sparse methods. What do you think we're missing to have more widely used neural+sparse approaches?
vlejd•2mo ago
I think the lack of efficient GPU kernels was the main problem. It is much, much easier to get a real speedup and memory reduction from quantization from fp16 to fp8 than from 50% sparsity. For sparsity you needed structure (which makes your model worse) and special hardware support.