HPCA Reproducibility

SkillDev tools

Use when strengthening HPCA reproducibility: pinning the result chain from simulator commit through config, workload, sampled region, and statistics, building one manifest per figure, recording machine state for silicon runs, and keeping the environment resurrectable for the IEEE artifact-badging round.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the HPCA Reproducibility skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in HPCA-Skills/skills/hpca-reproducibility/SKILL.md and read by ahel’s review.

Use this to make an HPCA paper's results reconstructable — by a reviewer during the window, by an artifact evaluator after acceptance, and by you six months later when the environment has drifted. HPCA's artifact badges are IEEE reproducibility badges earned on a separate AE HotCRP, so build toward that pipeline, not the ACM one.

Pin the result chain

Every figure in the paper should trace back through an unbroken chain:

simulator commit (or machine + firmware)
  -> configuration file (core, cache, DRAM, interconnect)
    -> workload + input + sampled region
      -> raw output logs
        -> statistics script
          -> the figure/table in the PDF

If any link is unpinned — a simulator built from "latest," a config edited by hand, a region chosen ad hoc — the result is not reproducible, only re-runnable by you.

One manifest per figure

Give each headline figure a manifest that names its commit, config, workload, region, seed/trial count, and the exact command that regenerates it. A regen.sh per figure that reproduces the artifact from raw logs turns "trust me" into "run this."

Chain linkWhat to pinFailure if unpinned
SimulatorCommit hash + local-patch diffSilent behavior drift between builds
ConfigVersioned file, not manual editsUnreproducible operating point
Workload/regionSuite version + sampling recipeCherry-picked region suspicion
StatisticsScripted, seededNumbers that cannot be regenerated
Silicon runsGovernor/turbo/SMT/NUMA + kernel/firmwareNoise mistaken for signal

Record machine state for silicon

A real-hardware result is only reproducible with its host state captured: frequency governor, turbo, SMT, NUMA policy, kernel and firmware versions, and the trial count with dispersion. Archive it next to the logs, not in your memory.

Handle non-redistributable workloads

SPEC-class and other licensed suites cannot ship in the artifact. Provide the recipe and checksums to reconstruct them, plus at least one freely available workload that exercises the full pipeline so an evaluator without a license can still reproduce a headline result.

Keep the environment resurrectable

Between submission and the badge round, environments rot. Containerize or script the build, pin dependency versions, and do a cold-start resurrection drill on a clean machine before you promise a reviewer or evaluator anything. The single rebuttal/revision window is not the time to discover your simulator no longer builds.

Reproducibility checklist

[Result chain] every figure pinned commit->config->workload->region->stats? (Y/N)
[Manifests] one per headline figure with a regen script? (Y/N)
[Silicon state] governor/turbo/SMT/NUMA + kernel/firmware + trials archived? (Y/N/NA)
[Licensed workloads] recipe+checksums + one free workload provided? (Y/N/NA)
[Resurrection] cold-start build drill passed on a clean machine? (Y/N)
[Badge readiness] packaged for the IEEE AE HotCRP? (Y/N)
[Top gaps] <ordered>

Reopen the current artifact-evaluation page for the badge set and calendar before relying on any AE detail here — the AE mechanics are per-edition.

Signals

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Item type
skill
Key
hpca-reproducibility
Source
github.com/brycewang-stanford/awesome-journal-skills