vllm-project/vllm

[Feature]: Use kernel abstraction for fp4 scaled mm

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#31,823 创建于 2026年1月6日

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 (12 评论) (0 反应) (1 负责人)Python (80,034 star) (16,816 fork)batch import
feature requesthelp wantedunstale

描述

🚀 The feature, motivation and pitch

See MPLinearKernel and ScaledMMLinearKernel.

Alternatives

No response

Additional context

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贡献者指南

技术栈
python
领域
backendmachine learningperformance
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
4
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
over 1 week
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
blocked
清晰度议题是否清楚说明期望改动、验收标准和下一步。
needs investigation
前置要求
Familiarity with vllm's linear kernel classesUnderstanding of fp4 quantizationCUDA kernel programming
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
15
研究方向
Examine the existing MPLinearKernel and ScaledMMLinearKernel implementations in the vllm codebase to understand the current kernel abstraction for scaled matrix multiplication. Then design a new kernel abstraction specifically for fp4 (4 bit floating point) scaled MM, considering the discussion in the issue comments (12 comments) for any design constraints or preferences. No pull requests are linked, so this is a clean design task. Key files to review: likely in vllm/model executor/layers/ or similar paths.