MLSys P0-4: fleet library (6 SKUs + 8-GPU node) and the reference admission program
Nobody has claimed this yet.
- Dominant language
- Rust
- Stars
- 14
- Forks
- 2
- Avg merge
- 12h 42m
- Merged PRs (30d)
- 61
Description
Part of the MLSys 2027 fleet-admission readiness set — see the tracking issue.
Why
This is where the paper's evidence comes from, and where "bug fixes here and there" actually lands. Writing real SKU declarations and a real admission program will flush const-eval and checker bugs that synthetic tests do not reach.
Scope
-
fleet/{a100-40,a100-80,h100-sxm,h200,b200,mi300x}.vx, from vendor spec sheets, citing them in comments - one 8-GPU node declaration with NVLink / PCIe / IB edges
- reference inference program: weights + KV + activations as const-generic arithmetic over (layers, heads, dim, dtype, context, batch, TP)
- file each bug found as its own issue and link it back here
The spec-sheet citations are not optional politeness — the paper's capacity numbers are only as credible as their provenance.
Estimate: ~1 week including fixes.
Depends on: fp8 element types, --machine flag.
Contributor guide
No contributing guide indexed for this repository
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.
Research direction
Start by checking the fp8 element-type and --machine prerequisites, then inspect the fleet/ declarations named in the scope. Add the six vendor-cited SKU files, the 8-GPU node edges, and the reference inference program; use the const-eval and checker behavior to identify issues, and file each discovered bug separately.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- rust
- Domain
- ai-infra-agents, compilers
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100