GPU Design · All levels

Latency Hiding & Occupancy: Review Checklist

Review Checklist for Latency Hiding & Occupancy.

Review checklist

Review Checklist for Latency Hiding & Occupancy centers on memory-latency cover ratio, long scoreboard stall %, and active warp depth. 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: performance lead, kernel engineer, compiler team.

Signoff ownership

diagram
GPU OWNERSHIP LAYERS — Latency Hiding & Occupancy

artifact area     owner
----------------  ----------------------------
architecture    performance lead
RTL/microarch   kernel engineer
software/tools  compiler team

Rule: each metric needs a named owner before signoff.

GPU deep dive

Warp scheduling quality determines whether latency hiding survives real control-flow and memory variance.

Concept diagram

diagram
WARP SCHEDULING LOOP

ready warp? -> issue -> dependency wait -> reconverge -> issue

Metric graph

diagram
STALL REASON SHARE

long scoreboard    ███████
divergence replay  █████
barrier wait       ███

Reports and artifacts

  • eligible warp ratio

  • stall reason histogram

  • barrier wait cycles

  • scheduler fairness report

Mini case study

A barrier-heavy kernel looked occupancy-safe, but warp arrival imbalance turned sync points into dominant stalls.

Debug branches

  • Compare scheduler policy traces under bursty workloads

  • Measure reconvergence delay and predication side effects

  • Quantify barrier idle time before tuning launch size

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 Latency Hiding & Occupancy, the minimum checklist is workload scope, memory-latency cover ratio, long scoreboard stall %, and active warp depth, artifact evidence (latency cover model, occupancy-vs-throughput curve, and stall reason timeline), 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.