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nano-vllm/tests
Zijie Tian a5307fb124 📝 docs: add CUDA Graph optimization plan for offload mode decode
- Update task_plan.md with 6-phase segmented graph implementation plan
- Add findings.md documenting 7 key discoveries about current implementation
- Add progress.md for tracking implementation progress
- Add test_chunk_attention_graph_reuse.py validating 2-graph reuse strategy

Key architecture decision: Split transformer layer into 3 segments:
- PRE-ATTENTION GRAPH: norm → qkv_proj → rotary (1 graph, reused)
- CHUNKED ATTENTION: H2D (eager) + flash_attn (2 graphs) + merge (eager)
- POST-ATTENTION GRAPH: o_proj → norm → FFN (1 graph, reused)

Total: 4 graphs serving all layers via copy_() tensor updates.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-22 02:12:24 +08:00
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2026-01-06 18:41:08 +08:00