측정: 익명 mmap의 cudaHostRegister 비용 (s/GiB)과 등록 버퍼의 H2D
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 42/100
- Issue type
- Feature
- Clarity
- Clearly specified
- Activity status
- Active
- Tech stack
- rust
- Domain
- backend, performance
Research direction
Start by reading the repository’s CUDA memory registration and host-to-device transfer paths, then check how existing benchmarks are structured; the issue does not name specific files or tests. Build a small C or Rust benchmark that measures cudaHostRegister for anonymous mappings of 1, 4, and 16 GiB and H2D throughput, recording the GPU, driver, OS, and RAM. If possible, check cudaHostRegisterPortable across two cards; done means publishing the source and measurements in s/GiB and GB/s.
Written by the indexing model from the issue text.
Description
익명 mmap 메모리를 cudaHostRegister(flags 0)로 등록하는 데 GiB당 몇 초가 드는지 재 주세요. 등록된 호스트 메모리는 카드로 바로 복사되어, expert 스왑이 호스트 DRAM을 세 번 지나지 않고 한 번만 지납니다. [유도] 값으로 V4.1은 토큰당 −0.27 ms, GLM은 −0.58 ms입니다.
- 할 일: 작은 C 또는 Rust 프로그램 하나. 익명 mmap으로 1, 4, 16 GiB를 잡고,
cudaHostRegister(flags 0)에 걸린 시간과 등록된 버퍼에서 카드로의 H2D GB/s를 잽니다. 가능하면cudaHostRegisterPortable로 카드 두 장에서 같은 버퍼를 쓸 수 있는지도. - 보고: s/GiB, H2D GB/s, GPU, 드라이버, OS, 호스트 RAM. 프로그램 소스도 함께 붙여 주세요.
- 하드웨어: CUDA 카드가 있는 아무 Linux 머신. DGX Spark와 카드 두 장인 머신이면 더 좋습니다.
- 판정: 0.02 s/GiB 미만이면 호스트 아레나 전체를 등록합니다. 그 이상이면 스왑 후보만 등록하거나 배경에서 등록합니다.
작업을 맡으실 분은 댓글로 알려 주세요. AI로 편하게 쓰셔도 됩니다(CONTRIBUTING.ko.md).
- Dominant language
- Rust
- Stars
- 21
- Forks
- 4
- Avg merge
- 3h 52m
- Merged PRs (30d)
- 134
Getting set up
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First steps
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- 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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