We just released AlgoPerf v1.0.1! 📚 New workload: AlgoPerf now includes a decoder-only 150M Language Model. ⚙️ Hardware switch: moving from 8xV100 to 4xA100. 🐞 Bug fixes and improved API. Coming soon: updated leaderboard with new optimizers! 👀

We just released AlgoPerf v0.6! 🎉 ✅ Rolling leaderboard ✅ Lower compute costs ✅ JAX jit migration ✅ Bug fixes & flexible API Coming soon: More contemporary baselines + an LM workload… github.com/mlcommons/al...

GitHub - mlcommons/algorithmic-efficiency: MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training a...

MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models. - mlcommons/algori...

github.com

We're all about acceleration! 😉 Watch @priya-kasimbeg.bsky.social & @fsschneider.bsky.social speedrun an explanation of the AlgoPerf benchmark, rules, and results all within a tight 5 minutes for our #ICLR2025 paper video on "Accelerating Neural Network Training". See you in Singapore!

Hi there! This account will post about the AlgoPerf benchmark and leaderboard updates for faster neural network training via better training algorithms. But let's start with what AlgoPerf is, what we have done so far, and how you can train neural nets ~30% faster.