feat: expose CUDA device attributes
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
Research direction
The work is already implemented in the linked NVlabs/cutile-rs pull request #255, which the issue says merges cleanly after rebasing; NVIDIA/cuda-rust's AGENTS.md describes how to transplant it. Read the "Transplanting a cutile-rs pull request" section and inspect the replayed changes and their GPU-gated test. Done means the changes are recreated in this repository and the listed formatting, check, and test commands pass.
Written by the indexing model from the issue text.
Description
Tracks pull request NVlabs/cutile-rs#255 (https://github.com/NVlabs/cutile-rs/pull/255) by @honeyspoon, opened 2026-09-01: feat: expose CUDA device attributes. The branch was rebased onto cutile-rs main on 2026-10-07 and merges cleanly.
@honeyspoon: that repository has moved here and is being archived, so the pull request is closed there, not rejected. If you want to continue the work, please recreate it against NVIDIA/cuda-rust. AGENTS.md in NVIDIA/cuda-rust has a "Transplanting a cutile-rs pull request" section that lets an agent do the replay (it fetches pull/255/head from NVlabs/cutile-rs, keeps your authorship and sign-off, and maps the moved paths).
Original description:
Why
Device exposes its L2 size, but querying related occupancy, bandwidth, and persisting-cache limits requires direct calls through cuda_core::sys.
What changed
- Add a non-exhaustive
DeviceAttributeenum. - Add safe
Device::attributeaccess to integer-valued CUDA device properties. - Cover compute capability, clocks, memory bus and cache limits, and per-SM occupancy resources.
- Route
l2_cache_size_bytesthrough the shared query path. - Add a GPU-gated test that queries every exposed attribute and checks the existing L2 helper against the generic result.
This extends the existing Device API only; it does not add context, stream, module, or launch abstractions.
Validation
cargo fmt --all -- --checkcargo check -p cuda-core --all-targetscargo test -p cuda-core --test device_attributes --no-runcargo test -p cuda-core --doc- full workspace Clippy, compile-only, and CPU suites passed before splitting the independent changes
- Dominant language
- Rust
- Stars
- 3.8k
- Forks
- 325
- Avg merge
- 5d 19h
- Merged PRs (30d)
- 73
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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