rust-gpu/rust-cuda

Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.

View on GitHub ↗Jump to charts ↓Open shareable report

Summary Information

Updated 20 minutes ago
Added to GitGenius on September 12th, 2026
Created on October 17th, 2021
Open Issues & Pull Requests: 96 (+0)
GitHub issues: Enabled
Number of forks: 245
Total Stargazers: 5,361 (+0)
Total Subscribers: 59 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 46.6 hours
Mean response time: 95.4 days
90th percentile: 324.3 days
Tracked items: 94

Most active contributors

Sign in to see contributor activity.

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 97% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 7% of issues opened in the past year have been closed. Three people close 88% of everything that gets resolved.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 34
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 438 days
Stale 30+ days: 34
Stale 90+ days: 29

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (8)
  • help wanted (7)
  • good first issue (5)
  • C-discussion (3)
  • bug (3)
  • A-atomics (1)
  • C-rustc_codegen_nvvm (1)
  • I-unsound 💥 (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Rust CUDA is an ecosystem of libraries and tools for writing and executing GPU code entirely in Rust.

The project addresses the challenge of GPU programming by enabling developers to write CUDA kernels and GPU applications using Rust instead of C or C++. This approach leverages Rust's memory safety guarantees and type system while targeting NVIDIA GPUs through the CUDA platform. The ecosystem provides the necessary abstractions and tooling to compile Rust code to GPU targets and execute it on CUDA-capable hardware.

Developers should approach this project understanding that it remains in early development with known bugs, safety issues, and incomplete functionality. It suits teams already invested in Rust who want to avoid context-switching to C or C++ for GPU work, or who prioritize Rust's safety properties in performance-critical code. The project is particularly relevant for those building GPU-accelerated applications where Rust's ownership model and compile-time guarantees provide value beyond what traditional GPU languages offer.

The project has been rebooted after a period of dormancy and is actively seeking contributions. Development is ongoing with status updates provided to the community, indicating renewed momentum and commitment to moving the ecosystem forward despite its early-stage maturity.