RA

rapidsai/raft

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

992 228 +2/wk
GitHub
anns building-blocks clustering cuda distance gpu information-retrieval linear-algebra llm machine-learning nearest-neighbors neighborhood-methods
Trend 3

Star & Fork Trend (20 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

rapidsai/raft has +2 stars this period . 7-day velocity: 0.2%.

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Metric raft pyGAM autogen-ui chronon
Stars 992 992991991
Forks 228 28613890
Weekly Growth +2 +1-2+0
Language Cuda PythonTypeScriptScala
Sources 1 111
License Apache-2.0 Apache-2.0MITApache-2.0

Capability Radar vs pyGAM

raft
pyGAM
Maintenance Activity 100

Last code push 0 days ago.

Community Engagement 100

Fork-to-star ratio: 23.0%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 52

+2 stars this period — 0.20% growth rate.

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.