Efficiently support mixed precision w8a16 models
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- Dominant language
- C++
- Stars
- 333
- Forks
- 150
- Avg merge
- 4d 19h
- Merged PRs (30d)
- 54
Description
Generalize the work to efficiently support w4a16, to support w8a16 (weights in an 8 bit format, e.g. int8, eventually fp8); activations in fp16 (eventually also bf16).
"Efficiently" here means that the weights will stay as int8, and they will be dequantized only in the context of the kernel that will use them; just like how it works for int4 weights.
Contributor guide
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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
No files, tests, or entry points are named. Start by locating the existing int4 and w4a16 handling, then trace how weights are represented and dequantized within the consuming kernel. Done means the approach is generalized to efficiently support w8a16 weights with fp16 activations while preserving the stated in-kernel dequantization behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100