GPU Design · All levels

Instruction Issue & Scoreboard: Review Checklist

Review Checklist for Instruction Issue & Scoreboard.

Review checklist

Review Checklist for Instruction Issue & Scoreboard centers on issue slot utilization, dependency stall ratio, and scoreboard wait 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: SM RTL owner, verification owner, performance lead.

Signoff ownership

diagram
GPU OWNERSHIP LAYERS — Instruction Issue & Scoreboard

artifact area     owner
----------------  ----------------------------
architecture    SM RTL owner
RTL/microarch   verification owner
software/tools  performance lead

Rule: each metric needs a named owner before signoff.

GPU deep dive

Shader-core throughput is gated by issue policy, register-bank access, and pipeline hazard behavior.

Concept diagram

diagram
SM CORE LOOP

warp schedulers -> issue ports -> ALU/FPU/Tensor pipelines
scoreboard + register file gate progress

Metric graph

diagram
SM BOTTLENECK MIX

dependency stalls   ███████
bank conflicts      ████
pipeline bubbles    ███

Reports and artifacts

  • SM IPC dashboard

  • issue stall taxonomy

  • register-bank conflict log

  • shader unit utilization

Mini case study

Compiler register allocation shifted operand banking, doubling RF conflicts and causing a 14% shader regression.

Debug branches

  • Inspect scoreboard wait-depth trends

  • Track RF conflicts by instruction class

  • Separate front-end issue loss from backend saturation

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 Instruction Issue & Scoreboard, the minimum checklist is workload scope, issue slot utilization, dependency stall ratio, and scoreboard wait depth, artifact evidence (scoreboard state timeline, issue reason breakdown, and stall attribution report), 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.