Chunk 66.1

In this chunk, the assistant systematically executed the user's three directives—fix CUDA graphs, optimize marshaling, and implement defrag—while continuously diagnosing and adapting to real performance data. First, it made the verify kernel **capture-safe** by rewriting it to consume SGLang's native static buffers directly (no host syncs, copies, or `cudaMalloc`), with a fixed `NSPLIT` and a torch-allocated workspace. CUDA graph capture succeeded in ~1.5 seconds, and decode now replays the graph correctly with generations matching the Triton baseline. Second, the "marshaling optimization" was redirected after the profiler revealed that CPU orchestration (tree-build at 1.8ms, mask-build at 0.18ms) was negligible—the real bottleneck was the verify attention itself, **occupancy-starved in the TP8 regime** (only 8 heads/rank). Two kernel tuning fixes—increasing `NSPLIT` from 16 to 64 and adding 128-bit vectorized bf16 KV loads—delivered a dramatic **3–6× end-to-end decode speedup** over Triton+graphs across all context lengths (4k–65k). Third, the assistant implemented **Tier 0 defrag** by monkeypatching the allocator to force `need_sort=True`, keeping per-request KV contiguous on churned pools, and confirmed it active on all 8 TP workers. Tier 1 (live relocation) was deferred with clear reasoning: single-request KV is already contiguous, and the bottleneck has now shifted to MoE expert imbalance at batch size 1. A key theme was the assistant's disciplined use of instrumentation to replace assumptions with evidence. The profiler disproved the CPU-orchestration theory and pinpointed the verify kernel's occupancy as the true cost, leading to targeted tuning that unlocked the 3–6× gain. The assistant also correctly interpreted the user's GPU utilization screenshots, confirming that prefill is compute-bound (all GPUs busy) while decode is now MoE-imbalanced after attention was fixed—a fundamental TP+low-batch limitation that batching or expert parallelism would address. The session closed with the live service running the owned capture-safe kernel at **3–6× Triton's decode throughput**, with CUDA graphs enabled, Tier 0 defrag active, and the bottleneck cleanly identified as MoE imbalance—a structural ceiling beyond the verify kernel's scope.

The Execution Phase: From Plan to 3–6× Decode Speedup on Blackwell Consumer GPUs 3088 words

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