TritonParse: A Compiler Tracer, Visualizer, and Reproducer for Triton Kernels
C-Rank Grade: D (Risky) - 30/100
External PR Merge Rate: -
Response Time: 9h
First Timer Success: -
meta-pytorch/tritonparse has a recorded first-timer success rate of 0.0%. Repositories ranked D typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in meta-pytorch/tritonparse respond to incoming external pull requests in approximately 8.9 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 29.9 places meta-pytorch/tritonparse in the D tier.
The external contributor pull request merge rate for meta-pytorch/tritonparse is 0.0%, based on public PR activity from non-core contributors.
meta-pytorch/tritonparse currently has 7 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Collaborative maintainer environment in meta-pytorch/tritonparse. Reviews community pull requests with focus on project quality.
Discussions in meta-pytorch/tritonparse focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.
Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.
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/meta-pytorch/tritonparse?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
Calculating local time...
Calculating local time...
Detected: UTC
Maintainers are most responsive around 16:00 UTC (16:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 15:00 to 19:00 UTC (15:00 - 19:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~6 hours (81% approval). Large PRs (>500 lines) take ~43 hours (29% approval). Keep your diff compact for rapid review.
Problem In the IR Code view, clicking a line highlights the corresponding lines in the other IR and Python panels. The viewer currently scrolls to the first highlighted line when necessary, but there is no way to see where the remaining highlighted lines are located across the full file. For large IR files or mappings containing multiple distant lines, users must manually scroll through the panel to find them. Steps to reproduce Open a trace containing source mappings. Go to the IR Code view. Click a line that maps to multiple lines in another panel. Observe that the panel may scroll to the first mapped line, while the locations of the other highlighted lines are not visible outside the viewport. Proposed behavior Add a slim VS Code-style overview ruler to each code panel. The ruler should: Show markers for every currently highlighted line. Position markers proportionally to their location in the full file. Update or clear markers whenever the line mapping changes. Allow clicking a
When a parsed trace is too large, e.g., a 700MB ndjson.gz, the website crashes. We should add an automatic file split function to divide a large trace into multiple files.
maybe we can just add a lable in the final parsed trace file name.
Rate what actually matters after opening a pull request here.
Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.
When evaluating whether to contribute to meta-pytorch/tritonparse, 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 meta-pytorch/tritonparse acknowledge new external contributions in approximately 8 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.
meta-pytorch/tritonparse has a recorded first-timer success rate of 0.0%. Repositories ranked Risky typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~8 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ 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 29.9 places meta-pytorch/tritonparse in the Risky tier.
The external pull request merge rate is 0.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, meta-pytorch/tritonparse currently has 7 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for meta-pytorch/tritonparse 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.