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rdna35 prefill optimizations other than mmq - #129

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liangliangchang wants to merge 9 commits into
gfx11from
lichang.rdna35-prefill-quant-rope
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liangliangchang wants to merge 9 commits into
gfx11from
lichang.rdna35-prefill-quant-rope

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Batch Qwen vision windows and tune guarded RDNA3.5 attention paths.
Fuse clamp conversion, normalization and activation packing, and
residual scaling while preserving existing dispatch and rounding.

Add backend coverage and document the matched VLM performance results.

Assisted-by: Codex
@liangliangchang liangliangchang changed the title Lichang.rdna35 prefill quant rope rdna35 prefill optimizations other than mmq Oct 7, 2026
Zero-pad compatible D72 self-attention to the existing D80 WMMA
kernel, retain the original attention scale, and extract D72 output.
Guard small workloads, unsupported layouts and attention features.
Add backend coverage for dispatch boundaries and fallback paths.

On gfx1151, Gemma-3-4B median HTTP TTFT improves from 1141.47 ms to
769.71 ms with context checkpoints enabled (32), using 20 timed
requests per configuration in ABBA order. D72 and D64/D80 backend
suites pass 909 and 224 cases; 32 generated token IDs match baseline.
Floating-point log probabilities differ with the WMMA arithmetic.

Assisted-by: Codex
Extend shared GLU producer kernels to SwiGLU and padded Q8 rows.
Use 128-thread blocks for eligible D128 Q/K norm-RoPE prefill.
Preserve existing dispatch, FP32 rounding and fallback paths.

On gfx1151 with checkpoints enabled, 3968-token HTTP TTFT falls
4.76% for Qwen2.5-3B and 3.85% for Qwen3-4B. Producer, graph and
generation checks pass with the recorded matching outputs.

Assisted-by: Codex
Document every branch optimization commit, structural eligibility,
measurement baseline and performance limits. Include the SwiGLU
results and distinguish isolated gains from combined experiments.

Assisted-by: Codex
@jimw567
jimw567 self-requested a review October 14, 2026 22:21
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