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Evaluating Large Language Models for CUDA Code Generation ComputeEval is a framework designed to generate and evaluate CUDA code from Large Language Models.

active 2025-04-102026-05-12 (UTC)

Partial coverage16,776 / 21,281 hourly files (79%) · 2 absent upstream · 4,504 failed, retryable2024-03-082026-08-12 (UTC)— sampled evenly across the window, so rankings and trends hold; absolute counts scale up.
Events
82
Pushes
5
Pull requests
5
Issues
2
Stars
52
Forks
5

Activity over time

Daily event counts in the loaded window

Line chart, 398 days from 2025-04-10 to 2026-05-12. Pushes: 5 total, peak 1 in a day. Pull requests: 5 total, peak 2 in a day. Issues: 2 total, peak 2 in a day. Comments: 2 total, peak 1 in a day. Stars: 52 total, peak 2 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
mggabel7421
dependabot[bot]4031
iquitap2000
sanannavyaa1100

Recent activity

Latest issues, pull requests and releases

  • Pull request#20dependabot[bot]2026-04-21 22:45
  • Pull request#20dependabot[bot]2026-04-21 22:45
  • Issue comment#12dependabot[bot]2026-03-17 19:37
    Bump pyasn1 from 0.6.1 to 0.6.2
  • Pull request#15dependabot[bot]2026-03-12 19:26
  • Pull request#11mggabel2026-03-12 19:25
  • Pull request#10mggabel2026-01-08 19:17
  • Issue comment#7mggabel2025-12-04 23:40
    compute-eval: correctness-focused benchmark, not performance-oriented?
  • Issue#2iquitap2025-05-22 03:03
    How is correctness (ground truth) evaluated in compute-eval?
  • Issue#2iquitap2025-05-22 02:56
    How is correctness (ground truth) evaluated in compute-eval?

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 52 stars here means stars gained during the window, not the repo's star count.