A tutorial on modern GPU programming for machine learning systems
C-Rank Grade: A (Welcoming) - 67/100
External PR Merge Rate: 85%
Response Time: 15h
First Timer Success: 100%
mlc-ai/modern-gpu-programming-for-mlsys has a recorded first-timer success rate of 100.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in mlc-ai/modern-gpu-programming-for-mlsys respond to incoming external pull requests in approximately 15.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 67.5 places mlc-ai/modern-gpu-programming-for-mlsys in the A tier.
The external contributor pull request merge rate for mlc-ai/modern-gpu-programming-for-mlsys is 85.2%, based on public PR activity from non-core contributors.
mlc-ai/modern-gpu-programming-for-mlsys does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Active maintainer team in mlc-ai/modern-gpu-programming-for-mlsys welcoming community pull requests and bug fixes.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/mlc-ai/modern-gpu-programming-for-mlsys?utm_source=github&utm_medium=badge)
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 14:00 UTC (14:00 UTC in your timezone). Recommended submission window is Tuesday - Thursday from 14:00 to 18:00 UTC (14:00 - 18:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~10 hours (96% approval). Large PRs (>500 lines) take ~73 hours (38% approval). Keep your diff compact for rapid review.
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When evaluating whether to contribute to mlc-ai/modern-gpu-programming-for-mlsys, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of mlc-ai/modern-gpu-programming-for-mlsys acknowledge new external contributions in approximately 15 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 85.2% were successfully merged into the primary branch.
mlc-ai/modern-gpu-programming-for-mlsys has a recorded first-timer success rate of 100.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~15 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rankâ„¢ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 67.5 places mlc-ai/modern-gpu-programming-for-mlsys in the Welcoming tier.
The external pull request merge rate is 85.2%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
mlc-ai/modern-gpu-programming-for-mlsys does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for mlc-ai/modern-gpu-programming-for-mlsys are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.