Flash Attention in ~100 lines of CUDA
In plain words
Flash Attention is a CUDA implementation that optimizes attention mechanisms in machine learning models through a streamlined, minimal codebase of roughly 100 lines. It targets developers and researchers working with neural networks who need faster attention computation on GPUs. What stands out is its simplicity and efficiency—achieving significant performance improvements while remaining compact and understandable, making it accessible for those wanting to understand or modify attention optimization at a low level.
written from the facts on this page · September 2026
More life & fun this month
the category →- TL
Life & fun · 10d ago · louisabraham.github.io
Photosynthesis fires two of your iPhone
Life & fun · 28d ago · photosynthesis.camera
SoloUno▲310Take control of hair pulling, nail biting & skin picking
Life & fun · 28d ago · solouno.io
Scroll through all 43,252,003,274,489,856,000 reachable Rubik's Cube permutations.
Life & fun · 26d ago · everycube.alen.is
Hi HN, I built Eigendrum, a web tool that solves the 2D wave equation for arbitrary shapes so you can hear what they sound like as drums. How it works: * Solves -∇²u = λu using finite element analysis (Kφ = λMφ) on a triangle mesh. * Validated to <0.1% error against closed-form solutions for circles (Bessel zeros) and rectangles. * Sound model factors in strike location, Rayleigh damping, and mallet width. * Includes Kac drums I & II to demonstrate identical sound spectra from different geometries. * No frameworks, build steps, or dependencies. Repo and tests:…
Life & fun · 27d ago · baselashraf81.github.io
Launched alongside, March 2024
the whole month →
- 3Y
Life & fun · 2024 · github.com
Microlaunch▲1,116Launch and get feedback on both the idea and product
Dev tools · 2024 · microlaunch.net
