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RayBNN_Sparse

v2.0.2 Growing

Sparse Matrix Library for GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI

GPL-3.0-only Edition 2021
Science #math#sparse#opencl#cuda#equation

Quick Verdict

  • โœ•Not updated for 1+ year
  • โœ“Stable API (2.x for 2+ years)
  • !Heavy dependency tree (24 direct deps)

Security

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Downloads
10.0K
Dependents
54
Releases
7
Size
26KB

Deep Insights

๐Ÿ“Š
Steady growth

61 downloads in the last 30 days (2/day), up 3% from the previous period.

โœ…
Stable for 2+ years

The API has been stable (1.x) for over 2 years with 7 releases. This level of maturity means you can depend on it without worrying about breaking changes.

๐Ÿ“ฆ
Heavy dependency tree

24 direct dependencies. Consider the impact on compile times and supply chain complexity.

๐Ÿ“
Compact crate

At 25KB, RayBNN_Sparse is lightweight. Small crate size correlates with focused, well-scoped functionality.

๐ŸŒŸ
Used by top crates

Notable dependents include RayBNN_Raytrace, RayBNN_Neural, RayBNN_Graph. When high-quality crates choose RayBNN_Sparse, it's a strong quality signal.

Health Breakdown

Maintenance 4/25

Recency, release consistency, active ratio

Quality 16/25

Yanked ratio, deps, size, maturity, features

Community 10/20

Reverse deps, ownership, ecosystem

Popularity 5/15

Downloads, momentum, growth trend

Documentation 10/15

Docs, repo, license, metadata

Download Trend

Daily downloads ยท last 90 days
2/day avg+12%
024681012/291/162/32/213/113/28

Top Dependents

Version Adoption

v2.0.2
28%
v0.1.5
22%
v0.1.4
17%
v0.1.2
16%
v0.1.1
16%

Release Timeline

7 releasessince 2023
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README

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Maintainers

Dependencies
24
direct dependencies
Dependents
54
crates depend on RayBNN_Sparse

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