GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
C-Rank Grade: B (Solid) - 57/100
External PR Merge Rate: 82%
Response Time: 3d
First Timer Success: 67%
SciML/DiffEqGPU.jl has a recorded first-timer success rate of 66.7%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in SciML/DiffEqGPU.jl respond to incoming external pull requests in approximately 70.5 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 56.6 places SciML/DiffEqGPU.jl in the B tier.
The external contributor pull request merge rate for SciML/DiffEqGPU.jl is 82.1%, based on public PR activity from non-core contributors.
SciML/DiffEqGPU.jl does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
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/SciML/DiffEqGPU.jl?utm_source=github&utm_medium=badge)
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Enter your branch size and test coverage below to forecast review turnaround and get 1-click git splitting commands.
Alternative open-source projects with active maintainers in Julia.
Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC.
A Julia package for fitting (statistical) mixed-effects models
An interface to various automatic differentiation backends in Julia.
No cached good first issues currently tracked for SciML/DiffEqGPU.jl.
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 SciML/DiffEqGPU.jl, 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 SciML/DiffEqGPU.jl acknowledge new external contributions in approximately 2 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 82.1% were successfully merged into the primary branch.
SciML/DiffEqGPU.jl has a recorded first-timer success rate of 66.7%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~2 days+. 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 56.6 places SciML/DiffEqGPU.jl in the Solid tier.
The external pull request merge rate is 82.1%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
SciML/DiffEqGPU.jl 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 SciML/DiffEqGPU.jl 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.