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

active 2025-12-102026-05-28 (UTC)

Partial coverage13,806 / 16,491 hourly files (84%) · 2 absent upstream · 2,685 failed, retryable2024-09-232026-08-11 (UTC)— sampled evenly across the window, so rankings and trends hold; absolute counts scale up.
Events
13
Pushes
8
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 170 days from 2025-12-10 to 2026-05-28. Pushes: 8 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
Stephen05125500
Zhuohang-Shen3300

Recent activity

Latest issues, pull requests and releases

  • Releasegithub-actions[bot]2025-12-10 20:51
    Continuous Analysis Run 20251210T205157Z

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.