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In this chunk, the assistant systematically root-caused a high-concurrency tool-call corruption in DeepSeek-V4-Flash-NVFP4 when using bf16 index keys under CUDA-graph capture. The investigation ruled out numerous hypotheses—including read kernel implementation, PDL store-read ordering, retraction/pool pressure, memory overlap, and PD transfer—through targeted A/B tests (fp8 vs bf16, eager vs captured) and subagent-led code analysis. The corruption was definitively localized to the interaction between CUDA-graph capture and the bf16 index-K buffer at decode batch sizes greater than one, with eager mode and fp8 remaining clean. A canary instrumentation was deployed that detected unexpected writes to index-K pages outside the expected store set, confirming buffer aliasing under replay. Key achievements include: establishing that the bug is bf16-specific and capture-dependent, eliminating the read kernel and store-ordering as causes, and deploying a real-time canary that catches the corruption mechanism in action. The canary revealed that at step 3546, 32 index-K pages changed when only 2 were expected, with 16 pages outside the legitimate range—a direct signature of external/aliasing writes during graph replay. This narrowed the remaining candidates to a replay write/placement hazard or a memory pool overlap affecting the 2× larger bf16 buffer. The overarching theme is a methodical, evidence-driven debugging process combining empirical testing, deep code inspection via subagents, and custom instrumentation. The assistant balanced rigorous hypothesis elimination with practical diagnostics, ultimately converging on a precise mechanism while keeping the path open to a robust workaround (running the indexer eagerly) if needed. The user’s preference for deep root-cause understanding guided the approach, with the canary providing the decisive evidence to move toward a targeted fix.

The Anatomy of a GPU Heisenbug: How Systematic Debugging Root-Caused a bf16 Corruption Under CUDA-Graph Capture 2186 words

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