AR
mratsim/Arraymancer
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
1.4k 100 +0/wk
GitHub
autograd automatic-differentiation cuda cudnn deep-learning gpgpu gpu-computing high-performance-computing iot linear-algebra machine-learning matrix-library
Trend
0
Star & Fork Trend (17 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
mratsim/Arraymancer has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | Arraymancer | TorchCraft | TextWorld | Personae |
|---|---|---|---|---|
| Stars | 1.4k | 1.4k | 1.4k | 1.4k |
| Forks | 100 | 210 | 194 | 340 |
| Weekly Growth | +0 | +0 | +0 | -1 |
| Language | Nim | C++ | Jupyter Notebook | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | NOASSERTION | NOASSERTION | MIT |
Capability Radar vs TorchCraft
Arraymancer
TorchCraft
Maintenance Activity 48
Last code push 97 days ago.
Community Engagement 36
Fork-to-star ratio: 7.2%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.