ppopp-reproducibility
Use when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds and warm-up, compiler/driver/flag provenance, and building an environment that reproduces the paper's scaling trend on different machines.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ppopp-reproducibility --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# PPoPP Reproducibility Build the reproducibility story that a parallel-performance paper needs. Unlike a deterministic algorithm, a PPoPP result depends on the **machine, the topology, and the run conditions** — and an evaluator or a future reader will not have your exact node. Reproducibility here means someone else can rebuild the environment and recover the **scaling trend and the relative comparison**, even when their absolute numbers differ. Pin everything you can at run time; you cannot reconstruct it after the machine is released. ## The environment description reviewers actually re-run State enough that a stranger could stand up the same experiment: ```text [CPU] exact model, sockets, cores/threads, base/turbo policy, NUMA node layout [Memory] size, channels, speed; per-socket bandwidth if it bounds you [GPU] model, count, driver + CUDA/ROCm version, connection (PCIe/NVLink) [Interconnect] for multi-node: fabric and topology [Software] OS + kernel, compiler + version + exact flags, libraries + versions, allocator [Runtime] thread count(s), pinning/affinity policy, scheduler settings, env vars ``` An evaluation whose machine is described only as "a Linux server" is the one
- The environment description reviewers actually re-run
- Control the sources of parallel non-determinism
- Reproduce the trend, not just the number
- Data and workloads
- Correctness reproducibility
- Pre-submission reproducibility pass
- Output format
What does the ppopp-reproducibility skill do?
Use when making a PPoPP paper's parallel-performance results reproducible, covering the hardware and topology description reviewers re-run, thread pinning and NUMA control, seeds and warm-up, compiler/driver/flag provenance, and building an environment that reproduces the paper's scaling trend on different machines.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ppopp-reproducibility --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 984 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.