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cpp

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更新日2026年5月31日 08:57

Host-side C++ kernels (`[build].language = cpp`) — the `solution/{kernel.cpp, binding.py}` two-file TVM-FFI binding pattern, and when to reach for it (host-side orchestration of a kernel you write, or composing CUTLASS headers into it). Distinct from the `cuda` skill which covers `.cu` device kernels compiled by nvcc. Use when writing a host-side C++ kernel or deciding cpp-vs-cuda.

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C++ host-side kernels

Reference for writing host-side C++ kernels (TVM FFI binding + kernel.cpp). Detailed guide: cpp.md.

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Reference for the active benchmark harness — what it IS and how it behaves (the active benchmark is flashinfer-bench). Covers config.toml structure (`[solution]`/`[build]`/`[benchmark]` tables), the status enum, the workload / fresh-inputs model, reference-baseline + scoring mechanics, tolerance keys, TVM-FFI builder link limits, and the silent-skip cascade. Invoke whenever you decode a bench status string, hit an unfamiliar config.toml field, suspect "correctness passed but the headline is implausible", or need to know what's frozen before proposing a bench edit — do NOT guess field or status semantics. Bench commands and noise methodology (A/B compare, variance check, drift cancellation) live in the `bench` skill.

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Run NVIDIA Nsight Compute (NCU) per-kernel profiling for register pressure, occupancy, stall-reason, memory-throughput, and IPC analysis. Use BEFORE architecting an optimization fix — not only after — when a hypothesis about microarchitectural behavior needs verification. NCU `Duration` is NOT comparable to bench timing; use NCU for ratios only.

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Run NVIDIA compute-sanitizer (memcheck / racecheck / initcheck / synccheck). FIRST action on `INCORRECT_NUMERICAL` or flaky output — rolling back destroys the evidence; sanitizer often points at the exact line. Also useful for diagnosing race conditions in multi-block kernels and uninitialized-memory reads.

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name	cpp
description	Host-side C++ kernels (`[build].language = cpp`) — the `solution/{kernel.cpp, binding.py}` two-file TVM-FFI binding pattern, and when to reach for it (host-side orchestration of a kernel you write, or composing CUTLASS headers into it). Distinct from the `cuda` skill which covers `.cu` device kernels compiled by nvcc. Use when writing a host-side C++ kernel or deciding cpp-vs-cuda.