docs(perf): capping the macOS decoder's threads is a loss, and why the fixture said otherwise - #597
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…e fixture said otherwise #592 proposed capping `thread_count` on the export's software decoder to give back the CPU-seconds that switching to it cost. Measured, it does neither: it does not return the CPU, and it costs the wall clock the decode change bought. decode threads cost CPU s auto (default) 1.044x 30.3 2 1.056x 29.2 1 1.775x 27.4 One thread is +70 % of wall clock to return 9.6 % of CPU — back near the 2.002x the shipped build measures. The premise was wrong: decoding N frames costs the same total work however many threads do it, so threads move wall clock and core occupancy, never CPU-seconds. The stage profile shows the mechanism. At one thread `decode.screen` goes 1.05 s -> 6.17 s while `enc.send_frame` goes 7.61 s -> 2.16 s: the decoder eats the slack an encoder-bound pipeline was leaving it, and the total holds — until the slack runs out, which on real content it does. A SECOND HAZARD, and the one worth reading. This experiment was run first on the generated fixture and concluded thread count did not matter at all (one thread: -0.0 % wall, -12.6 % CPU). The same experiment on the public bundle inverts it. The fixture is flat fills and sharp text, built to exercise the compositor; it is trivially decodable, so the decoder was never near being the constraint and the knob had nothing to act on. Every gate on that run was clean — drift, spread, output equality — on an answer that was wrong. Match the fixture to the stage under test. The known gap on energy is corrected at the same time. It said the CPU jump was 3.5x the energy; it is not a proxy at all, and the jump is not waste either — VideoToolbox does the same decoding in a fixed-function block that CPU accounting never sees, so the work moved somewhere visible and got 12x faster on the way. What capping threads would buy is lower peak core occupancy, which is a different question and still unmeasured.
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Included review availability: Your plan provides up to 8 included reviews per hour; 6 remain after this review. 📝 WalkthroughWalkthroughThe rendering performance documentation adds decoder fixture guidance, records macOS decoder thread-cap results, and clarifies that CPU-seconds do not represent VideoToolbox energy use. ChangesRendering performance measurement findings
Estimated code review effort: 1 (Trivial) | ~5 minutes Merge Risk: ⚪ Minimal · up to The documentation clarifies decoder-thread measurements, fixture limitations, and CPU accounting without indicating an unresolved product or runtime risk. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
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In `@technical-documentation/engineering/rendering-performance.md`:
- Line 583: Update the conclusion in the rendering-performance discussion to
acknowledge that reducing threads lowers CPU-seconds slightly, from 30.3 to 27.4
(9.6%), while substantially increasing wall-clock time. Replace the absolute
claim that threads never affect CPU-seconds, preserving the measured tradeoff
and recommendation against re-proposing the optimization.
- Line 575: Update the “What it was” description to call thread_count = 0 an
automatic thread count rather than one thread per core, unless the measured
build explicitly recorded that worker count; preserve the surrounding
performance measurements and conclusions.
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… thread count Two review findings, both of them catching me overstating my own measurement. **"threads move wall clock and core occupancy, never CPU-seconds" is contradicted by the table directly above it.** CPU-seconds go 30.3 → 27.4 at one thread — a 9.6 % fall. The premise was wrong about the size of the effect, not its sign, and the text now says so: threads mostly redistribute the decode work rather than reduce it, which is why 8× fewer of them buys ~10 % rather than ~90 %. That last 10 % is plausibly the thread pool's own overhead, but it was not isolated, so it is now marked unexplained rather than asserted. **`thread_count = 0` was described as "one thread per core".** libavcodec documents it as *automatic* — the decoder chooses, from the CPU count and its own threading model — and the number it actually picked was never read back. The doc says that instead of inventing a mapping. Neither changes the conclusion: one thread costs +70 % of wall clock, and the default stays.
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Both findings checked, both right, and both caught me overstating my own measurement. Fixed. 1. "threads move wall clock and core occupancy, never CPU-seconds" is contradicted by the table directly above it. CPU-seconds go 30.3 → 27.4 at one thread. That is a 9.6 % fall, not zero, and writing "never" while printing the number two lines up is exactly the kind of claim a reader should not have to catch for me. The corrected statement: the premise was wrong about the size of the effect, not its sign. Threads mostly redistribute the decode work rather than reduce it, which is why 8× fewer of them buys ~10 % and not ~90 %. And the ~10 % that does disappear is now marked unexplained — thread-pool overhead is the plausible reason, but I did not isolate it, so it should not read as established. 2. Neither changes the conclusion — one thread costs +70 % of wall clock, and the default stays — but both change what the document claims to know, which is the part that matters in a measurement record. |
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Records the answer to #592 (now closed) and the methodology mistake that nearly gave the opposite one. Documentation only.
Capping the decoder's threads does not work
#592 proposed capping
thread_counton the export's software decoder to return the CPU-seconds that switching to it cost. Measured on the public bundle, three cycles with an ffmpeg floor inside each, closing drift 0.9979, output identical across variants:One thread costs +70 % of wall clock to return 9.6 % of CPU — back near the 2.002× the shipped build measures.
The premise was simply wrong, and it was mine: decoding N frames costs the same total work however many threads do it. Threads move wall clock and core occupancy, never CPU-seconds. The stage profile shows the mechanism cleanly — at one thread
decode.screengoes 1.05 s → 6.17 s whileenc.send_framegoes 7.61 s → 2.16 s, the decoder eating the slack an encoder-bound pipeline left it, until the slack runs out.The hazard is the part worth reading
This experiment was run first on the generated fixture, and it gave the opposite answer — one thread measured −0.0 % wall, −12.6 % CPU, which reads as "the decoder has so much slack the knob does nothing".
The fixture is flat fills and sharp text, built to exercise the compositor. It is trivially decodable, so the decoder was never near being the constraint and the knob had nothing to act on. Every gate on that run was clean — drift, spread, output equality — on an answer that was wrong.
New rule in Measurement hazards: match the fixture to the stage under test.
The energy gap is corrected too
The entry said the 3.5× CPU jump was "roughly 3.5× the energy". It is not a proxy — and the jump is not waste either: VideoToolbox does the same decoding in a fixed-function block that CPU accounting never sees, so the work did not grow, it moved somewhere visible and got 12× faster on the way. What capping threads would buy is lower peak core occupancy, which is a different question and still unmeasured.
What a reviewer should push back on
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