GPU Design · All levels

Silicon Bring-up for GPU: Review Checklist

Review Checklist for Silicon Bring-up for GPU.

Review checklist

Review Checklist for Silicon Bring-up for GPU centers on time-to-first-frame/kernel, bring-up failure rate, and debug closure velocity. The objective is to connect profiler evidence to root-cause mechanism and release-safe action.

  • Workload scope and target KPI are explicitly documented.

  • Profiler + counter evidence is reproducible with revision tags.

  • Bottleneck classification is proved with mechanism-level traces.

  • Mitigation includes owner, blast radius, and rollback criteria.

  • End-to-end benchmark matrix confirms closure.

  • Owners signed: bring-up lead, firmware owner, driver team.

Signoff ownership

diagram
GPU OWNERSHIP LAYERS — Silicon Bring-up for GPU

artifact area     owner
----------------  ----------------------------
architecture    bring-up lead
RTL/microarch   firmware owner
software/tools  driver team

Rule: each metric needs a named owner before signoff.

GPU deep dive

Performance claims need verification-grade reproducibility, not one-off profiler screenshots.

Concept diagram

diagram
PERF VERIFICATION LOOP

benchmark -> profile -> optimize -> verify correctness -> regress

Metric graph

diagram
RELEASE READINESS

benchmarks stable     █████████
accuracy gates pass   ████████
perf regressions open ███

Reports and artifacts

  • golden benchmark suite

  • deterministic replay log

  • perf regression dashboard

  • accuracy/perf gate status

Mini case study

A kernel passed microbenchmarks but failed production SLA due to host-device sync overhead hidden from isolated tests.

Debug branches

  • Enforce end-to-end benchmarks alongside kernels

  • Pair every speedup with accuracy diff checks

  • Promote only reproducible profiler baselines

Senior review question

Ask: which metric and benchmark pairing proves this topic is truly closed in production context?

Key takeaways

  • Always pair micro-kernel metrics with end-to-end workload impact.

  • Lock toolchain, driver, and launch metadata before comparing performance results.

Common pitfalls

  • Optimizing occupancy without checking memory-system saturation.

  • Comparing profiler captures from different driver or compiler builds.

  • Declaring wins without reproducible accuracy and performance gates.

Review checklist explanation

A checklist is not bureaucracy here; it is how GPU teams avoid confusing local wins with product wins. Every signoff item should protect against a known class of false confidence.

For Silicon Bring-up for GPU, the minimum checklist is workload scope, time-to-first-frame/kernel, bring-up failure rate, and debug closure velocity, artifact evidence (bring-up checklist, boot trace timeline, and first-pass debug triage log), bottleneck classification, owner, rollback path, and full matrix validation.

If the change affects architecture or RTL, include correctness and PPA evidence. If it affects compiler/runtime policy, include compatibility and deployment evidence. If it affects physical design, include timing, IR, thermal, and observability evidence.