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- scripts/bench/compare.py: diff criterion medians (target/criterion/**/estimates.json) vs a committed baseline, print a markdown table to the job summary, flag >threshold regressions, always exit 0 (shared CI hardware is too noisy to gate on). --update rewrites the baseline. - ci.yml `bench` job: runs Tier-1 (criterion) + Tier-2 (loss-harness FEC recovery) GPU-free in the rust-ci container, then compare.py — report-only visibility per push/PR. - scripts/bench/gpu-stream.sh + bench-gpu.yml: Tier-3 real pipeline (virtual output → zero-copy → NVENC → punktfunk/1 → reassemble) on a self-hosted GPU runner; captures encode_us/tx_mbps/ send_dropped + client capture→reassembled latency, compares to gpu-baseline.json (20% threshold). Needs the dev box registered as a `[self-hosted, gpu]` act_runner (one-time, see the workflow header) — the dedicated hardware makes its absolute baseline meaningful, unlike shared CI. - baseline.json: dev-box Tier-1 numbers. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
33 lines
1.4 KiB
YAML
33 lines
1.4 KiB
YAML
# Tier-3 real-world GPU benchmark — the actual capture → zero-copy → NVENC → punktfunk/1 → reassemble
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# pipeline, measuring encode time / throughput / end-to-end latency. The GPU-less CI containers
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# (ci.yml `bench` job) can only run the Tier-1/2 GPU-free benchmarks; this runs on a SELF-HOSTED GPU
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# runner — a dev box with an NVIDIA GPU + a KWin session.
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#
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# Runner setup (one-time, on the GPU box): register a Gitea act_runner with the labels below, e.g.
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# act_runner register --instance https://git.unom.io --token <REPO_RUNNER_TOKEN> \
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# --labels gpu:host --name <box>-gpu
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# It runs jobs directly on the host (no container) so it can reach the GPU, PipeWire and the
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# compositor. A persistent KWin session helps (else the script brings up a headless one).
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#
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# Report-only: the script flags regressions vs scripts/bench/gpu-baseline.json but never fails the
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# job. Refresh the baseline on the runner with `scripts/bench/gpu-stream.sh <mode> <secs> --update`.
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name: bench-gpu
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on:
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workflow_dispatch:
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inputs:
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mode:
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description: "stream mode WxHxHz"
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default: "1920x1080x120"
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schedule:
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- cron: "0 6 * * *" # nightly
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jobs:
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gpu-stream:
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runs-on: [self-hosted, gpu]
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timeout-minutes: 20
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steps:
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- uses: actions/checkout@v4
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- name: Tier-3 GPU stream benchmark
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run: bash scripts/bench/gpu-stream.sh "${{ inputs.mode || '1920x1080x120' }}" 12
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