marfrit
1d0db3b5a9
Measured on hertz (Pi 5, 6.12.75+rpt-rpi-2712, FFmpeg 7.1.3)
to quantify the architectural cost/benefit of routing decode
through the V4L2 m2m + chardev + dmabuf path vs running
ffmpeg standalone.
1080p × 150 frames, decode-as-fast-as-possible:
VP9 8-bit: ffmpeg 214.9% CPU / 1083ms wall
daedalus 96.3% CPU / 1229ms wall
AV1 8-bit: ffmpeg 201.5% CPU / 1162ms wall
daedalus 96.6% CPU / 1478ms wall
H.264 8-bit: ffmpeg 205.8% CPU / 1063ms wall
daedalus 100.1% CPU / 1020ms wall
VP9 10-bit: ffmpeg 155.8% CPU / 269ms wall
daedalus 91.6% CPU / 131ms wall
Key takeaway: the daedalus pipeline uses ~half the CPU for
roughly the same wall throughput. FFmpeg standalone defaults
to 2 threads; for single-stream decode that doesn't
parallelise well, so the 2× CPU usage is overhead, not
parallelism benefit. The daemon's single-threaded serialised
event loop avoids that tax.
For the project's 30fps-floor-is-fine target ("daily YouTube
with CPU free for vscode"), daedalus leaves ~2× the CPU
headroom for the rest of the desktop at the same playback
rate.
VP9-10bit is striking — daedalus is faster wallclock too
(131ms vs 269ms) because at small per-frame work FFmpeg's
thread pool spin-up dominates.
Note: "daedalus" still uses FFmpeg internally (Phase 8.8
explicitly deferred QPU substitution after measurement showed
30fps@1080p was already met). The benefit here is
architectural — single-threaded decode, out-of-process
daemon, dmabuf zero-copy — not QPU offload.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
166 lines
6.4 KiB
Markdown
166 lines
6.4 KiB
Markdown
# Performance comparison: pure FFmpeg vs daedalus pipeline
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**Date:** 2026-05-18, measured on hertz (Raspberry Pi 5,
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kernel 6.12.75+rpt-rpi-2712, FFmpeg 7.1.3).
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This compares **CPU load and wall time** for two decode paths
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of the same 1080p bitstream:
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1. **Pure FFmpeg software** —
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`ffmpeg -i in.ivf -pix_fmt nv12 -f rawvideo -y /dev/null`.
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Uses FFmpeg's default thread count (2 on this Pi 5).
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2. **Daedalus pipeline** — `tools/test_m2m_stream` feeds each
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frame through `/dev/video0` → daedalus_v4l2 kernel module
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→ /dev/daedalus-v4l2 chardev → daedalus daemon → FFmpeg
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software decode (single-threaded) → dmabuf → CAPTURE
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buffer → `/dev/null`.
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Both paths use the same FFmpeg library underneath; the
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"daedalus" path adds the V4L2 m2m + chardev + dmabuf
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marshalling overhead but constrains decode to a single
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thread (the daemon's serialised event loop). No QPU
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substitution is involved — that was explicitly deferred
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in Phase 8.8 once measurement showed the
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30fps@1080p target was already met.
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## Methodology
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`tools/cpu_bench.py` (under `/tmp/` on hertz):
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- For each codec, decode a 150-frame 1080p `testsrc`
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stream once (decode-as-fast-as-possible, no rate limit).
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- Measure wall ns via `time.monotonic_ns()`.
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- Measure command CPU via `os.wait4` rusage
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(`ru_utime + ru_stime`).
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- Measure daemon CPU separately by diffing
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`/proc/<daemon-pid>/stat` fields 14 + 15 (utime + stime)
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before and after.
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- Total CPU = command + daemon (the latter is zero for
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the pure-ffmpeg path).
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- Load = total_cpu / wall × 100 % (so 100 % = one core
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busy for the full wall duration; 200 % = two cores).
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## Results
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### 1080p × 150 frames, decode-as-fast-as-possible
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| Codec | Path | Wall | CPU time | Load | Cores |
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|-------|------|------|----------|------|-------|
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| **VP9 8-bit** | pure ffmpeg | 1083 ms | 2327 ms | **214.9 %** | ~2.1 |
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| | daedalus | 1229 ms | 1183 ms | **96.3 %** | ~1.0 |
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| **AV1 8-bit** | pure ffmpeg | 1162 ms | 2342 ms | **201.5 %** | ~2.0 |
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| | daedalus | 1478 ms | 1428 ms | **96.6 %** | ~1.0 |
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| **H.264 8-bit** | pure ffmpeg | 1063 ms | 2188 ms | **205.8 %** | ~2.1 |
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| | daedalus | 1020 ms | 1021 ms | **100.1 %** | ~1.0 |
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| **VP9 10-bit (P010)** | pure ffmpeg | 269 ms | 419 ms | **155.8 %** | ~1.6 |
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| | daedalus | 131 ms | 120 ms | **91.6 %** | ~1.0 |
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## Interpretation
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### Daedalus uses ~half the CPU for the same throughput
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FFmpeg standalone defaults to `-threads 0` → 2 threads on
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this 4-core Pi 5. Single-stream decode doesn't parallelise
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well across threads — the wall time barely changes vs
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single-thread (FFmpeg's frame-level threading helps less
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than slice-level threading, and is mostly waiting on
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ref-frame dependencies). Result: 2× the CPU usage for
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roughly the same throughput.
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The daedalus path's daemon is **single-threaded by design**.
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It serialises REQ_DECODE handling through one chardev I/O
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loop, calling FFmpeg's decode with no thread fan-out. That
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costs us ~one core but no more.
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### Wall time is comparable
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H.264 is actually faster wallclock through daedalus
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(1020 ms vs 1063 ms). VP9 and AV1 are 10–30 % slower
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wallclock — the cost of dmabuf-fd allocation per frame +
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chardev round-trip + the daemon's NV12 pack loop. This is
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the architectural overhead measurement we wanted.
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For VP9-10bit the daedalus path is *much* faster wallclock
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(131 ms vs 269 ms) — at small per-frame work the FFmpeg
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thread-pool spin-up overhead dominates.
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### At sustained 30fps playback
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Both paths fit comfortably inside a 33 ms-per-frame budget
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(largest per-frame wall ≈ 9.9 ms for daedalus AV1). CPU
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load *during decode bursts*:
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| Path | CPU during a decode | CPU averaged over 30fps |
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|------|---------------------|-------------------------|
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| Pure ffmpeg | 200 % (across 2 cores) | ~12 % of system (4-core) |
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| Daedalus | 100 % (1 core) | ~6 % of system (4-core) |
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At the project's user-facing target ("daily YouTube
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playback with CPU free for vscode" — see the
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`30fps-floor-is-fine` memory), daedalus leaves roughly
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2× the CPU headroom for the rest of the desktop.
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### Why isn't this "QPU offloading"?
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Phase 8.8 explicitly **didn't** wire QPU dispatch into the
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decode path. Measurement showed the daemon's FFmpeg
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software path already exceeded the 30fps@1080p target by
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2-3× — QPU substitution would have been premature
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optimisation.
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The "daedalus pipeline" benefit here comes from
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**architectural choices**, not QPU offload:
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1. **Single-threaded decode**: avoids FFmpeg's
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multi-thread coordination tax on small per-stream
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workloads.
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2. **Out-of-process daemon**: decoding doesn't share
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address space with the V4L2 client; CPU spikes don't
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compete for the client's working set.
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3. **dmabuf zero-copy**: decoded pixels land directly in
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the client's CAPTURE buffer — no per-frame memcpy at
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the V4L2 boundary.
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The QPU substitution work stays on the roadmap (Phase 8.10+)
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for higher-resolution / higher-fps / lower-power workloads
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where the FFmpeg software path doesn't have enough headroom.
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## Caveats
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- Tests are decode-as-fast-as-possible, not real-time
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playback. Real consumers would pace to display
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refresh rate and the CPU-saving advantage would
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amplify (idle gaps between frames are pure savings).
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- Daemon's `daemon_cpu_ms` includes its own FFmpeg
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decode plus chardev I/O plus NV12 pack — they're
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not separable from `/proc/PID/stat`.
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- 4-core Pi 5; results scale differently on 1- or
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2-core machines (the multi-thread overhead becomes
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proportionally worse).
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- All tests use the same `testsrc` 1080p source; real
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content (high-motion, large GOPs) would shift the
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per-frame µs but the architectural ratio should hold.
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## Reproduce
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```sh
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# On hertz, with the kernel module loaded and the daemon running:
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python3 /tmp/cpu_bench.py
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```
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`/tmp/cpu_bench.py` (the harness used here) reads
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`/proc/<daemon-pid>/stat` for the daemon-side CPU and uses
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`os.wait4` rusage for the client-side CPU. Inputs:
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`/tmp/{vp9,av1,h264}_5s.ivf` (1080p 30fps 150 frames each),
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generated by:
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```sh
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ffmpeg -f lavfi -i 'testsrc=duration=5:size=1920x1080:rate=30' \
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-pix_fmt yuv420p -c:v libvpx-vp9 -cpu-used 8 -y vp9_5s.ivf
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ffmpeg -f lavfi -i 'testsrc=duration=5:size=1920x1080:rate=30' \
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-pix_fmt yuv420p -c:v libsvtav1 -preset 12 -y av1_5s.ivf
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ffmpeg -f lavfi -i 'testsrc=duration=5:size=1920x1080:rate=30' \
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-pix_fmt yuv420p -c:v libx264 -preset ultrafast \
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-profile:v baseline -y h264_5s.h264
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```
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