mudler / mudler/vllm.cpp

GFX1100-TG200: fuse silu-mul with Q8_K quant epilogue (VT_SILU_QUANT_FUSED)

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Dominant language
C++
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20h 26m
Merged PRs (30d)
310

Description

Row: GFX1100-TG200

Summary

Fuse the MLP silu(gate)*up activation with the Q8_K quantization epilogue on ROCm, eliminating the standalone QuantizeQ8KKWarpCoop launch for the ffn_down GEMV's activation input.

Lever

VT_SILU_QUANT_FUSED=1 (default OFF). When enabled, SiluMulQuantQ8KKWarpCoop produces both the bf16 activation and the Q8_K scratch in a single kernel, deleting the separate quant launch (~8.9us).

Benchmark

A/B interleaved, 5 pairs, Qwen3.5-4B Q4_K_M, 256 tokens, temp 0, seed 0:

A (T25 chain) B (T25+SiluQuant) Delta
Median 32.41 32.39 -0.08%

Noise — the fusion saves a launch but the benchmark is decode-dominated and the quant launch is amortized.

Token identity

PASS — identical output to T25 chain on The capital of France is with --max-tokens 32 --temperature 0 --seed 0.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Locate the ROCm implementations of SiluMulQuantQ8KKWarpCoop and QuantizeQ8KKWarpCoop, then trace the ffn_down activation path and the VT_SILU_QUANT_FUSED lever. Verify that the fused path produces both bf16 activation and Q8_K scratch without the standalone quantization launch, while preserving token identity and the reported benchmark behavior.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
machine-learning, performance
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
48/100

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