Repository Head-to-Head
control-toolbox/OptimalControl.jl vs JuliaGPU/JACC.jl
Objective C-Rank™ telemetry comparison benchmarked across PR merge rates, reviewer latency, maintainer breadth, and newcomer hospitality.
Export & Share•Share head-to-head metrics on GitHub or social media
Should I Contribute? Showdown Verdict
JuliaGPU/JACC.jl WinsExternal PR Merge Rate
92.9%vs88.9%
Median Review Latency
0.0hvs0.0h
90-Day Bus Factor
4vs5
Verdict computed from external PR merge rate, median review latency, and 90-day bus factor; ties broken by recent commit (PR) velocity. View share card image
JuliaS Tier (77%)
control-toolbox/OptimalControl.jl
Model and solve optimal control problems in Julia, both on CPU and GPU.
External PR Merge Rate92.9%
Review Latency (p50)0.0h
90-Day Bus Factor4 Maintainers
Onboarding Readiness0/100
JuliaS Tier (75%)
JuliaGPU/JACC.jl
CPU/GPU portable array, parallel_for/parallel_reduce in Julia for productive science. Funded by the US DOE Advanced Scientific Computing Research (ASCR).
External PR Merge Rate88.9%
Review Latency (p50)0.0h
90-Day Bus Factor5 Maintainers
Onboarding Readiness0/100