NVIDIA/cuda-rust - Open Source PR Review Scorecard

NVIDIA's CUDA platform for Rust. Host runtime crates plus Tile (cutile-rs) and SIMT (cuda-oxide) kernel programming models in idiomatic Rust.

C-Rank Grade: B (Solid) - 51/100

External PR Merge Rate: 10%

Response Time: 3h

First Timer Success: -

Frequently Asked Questions

Is NVIDIA/cuda-rust welcoming to first-time open-source contributors?

NVIDIA/cuda-rust has a recorded first-timer success rate of 0.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in NVIDIA/cuda-rust respond to incoming external pull requests in approximately 3.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 50.6 C-Rank™ score (B Tier) represent?

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 50.6 places NVIDIA/cuda-rust in the B tier.

What is the external contributor pull request merge rate for NVIDIA/cuda-rust?

The external contributor pull request merge rate for NVIDIA/cuda-rust is 10.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in NVIDIA/cuda-rust?

NVIDIA/cuda-rust currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

NVIDIA
NVIDIA/cuda-rustB•Solid3.7k
GitHub
Back to Explorer
NVIDIA

NVIDIA/cuda-rust

3,700
Active (30d)B•Solid(51/100)Low Sample (<20 PRs)Rust

NVIDIA's CUDA platform for Rust. Host runtime crates plus Tile (cutile-rs) and SIMT (cuda-oxide) kernel programming models in idiomatic Rust.

GitHub
Compare••
Jump to:

AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.5/10
Patience Score
8.2/10
Nitpick Rate
20%

Collaborative maintainer environment in NVIDIA/cuda-rust. Reviews community pull requests with focus on project quality.

What Contributors Actually Say

Discussions in NVIDIA/cuda-rust focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.

Hidden Friction Signals

Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.

Unwritten Rules

  • •1) Keep PR scope strictly aligned with the linked issue.
  • •2) Ensure local linters pass before opening a review.
  • •3) Maintain full test coverage for modified logic.

Top PR Submission Do's

  • •Add or update tests for changed behavior before requesting review
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not leave requested test coverage unresolved
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
3 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
10.0%
Selective PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
0.0%
No first-timer merges recorded in window

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
8 core
Highly collaborative maintainer core
Diagnostic Health HUD
10.0%
Merge Gauge
0.0%
1st-Timer
Community Vibe32/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for NVIDIA/cuda-rust
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/NVIDIA/cuda-rust)](https://getmerged.abhishekco.de/NVIDIA/cuda-rust?utm_source=github&utm_medium=badge)

Active Good First Issues (1)

View on GitHub

Summary #668 ("docs(examples): tma_multicast does run on consumer Blackwell", merged 2026-08-06) corrected the tma_multicast example on the strength of your RTX 5090 measurement: the sm_100a tma_multicast PTX JIT-loads and passes on an RTX 5090, so the "consumer Blackwell does not support TMA multicast" fallback text is outdated It fixed the two places it found — the module header and the runtime println! — and missed README.md entirely. That file still carries four separate assertions of the claim #668 removed, so the example's own directory now contradicts itself. My PR, my miss; filing rather than fixing blind because the second half below needs a call I cannot make. The four stale passages All in crates/rustc-codegen-cuda/examples/tma_multicast/README.md: 1. L116 — heading groups sm_120 with the failing case ### On Consumer Blackwell (sm_120) or Hopper (sm_90): 2. L119-124 — a sample transcript showing a failure you measured as a success GPU Compute Capability: sm_120

📅 Opened Aug 17, 2026💬 4 comments
Quality: 75/100Contribute
Looking for more Rust beginner tasks?Explore Rust GFI

Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

3 ratings required
Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for NVIDIA/cuda-rust

When evaluating whether to contribute to NVIDIA/cuda-rust, 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 NVIDIA/cuda-rust acknowledge new external contributions in approximately 3 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 10.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to NVIDIA/cuda-rust

01

Is NVIDIA/cuda-rust welcoming to first-time open-source contributors?

NVIDIA/cuda-rust has a recorded first-timer success rate of 0.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~3 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 50.6 C-Rank™ score represent?

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 50.6 places NVIDIA/cuda-rust in the Solid tier.

04

What is the external contributor pull request merge rate for NVIDIA/cuda-rust?

The external pull request merge rate is 10.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in NVIDIA/cuda-rust?

Yes, NVIDIA/cuda-rust currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for NVIDIA/cuda-rust 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.