7d365b3ff58c6653a510d5818c695e07d5a8a896
11
Commits
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7d365b3ff5 |
Drop SASI on capacity, then find the budget never had the disk in it
USER DECISION: drop the `sasi` profile. Not on bandwidth -- on capacity. A SASI volume is 40 MB, and the 22.8 min of unique scene footage on the source Blu-ray (streams 00000-00201, measured, not recalled) is 146 MiB at the LOWEST rate this codec makes -- more than the machine's whole 4-unit SASI space. `scsi` is the only profile now. FINDINGS 32. Then the user asked whether we were drawing the wrong conclusions about PIO vs DMA, and we were, more broadly than the question implied. Every CPU figure in FINDINGS 24-34 is scored against the full 833,333 cycles/frame with nothing subtracted for moving the bitstream off disk. Debiting the HD63450 cycle-steal at the long-standing 8 clk/word ESTIMATE, "1 frame of 120 misses" becomes 84 of 120, median 112.4%. PIO at the span rate is 99.8% of the machine. Spans buy cycles by spending bandwidth and the bandwidth returns as steal, so 31.6's "fits completely" becomes a worst frame of 114.3%. 10 fps absorbs it: median 93.7%, 1/120. FINDINGS 35. `11_cpu_budget.py` takes --io dma|pio|none, defaults to dma, and warns if asked for none. Also landed: - item 1 done: the cost model checked against the 68000 on a cost-aware container, -3.07% to +0.01%, whole-window mean -1.22%. FINDINGS 34. - item 4 done: the container carries its own 4-byte record alignment (DLX2). 94/120 record starts were on odd addresses -- an address error, not a slow read -- now 0/120 for 16 B/s. Re-encoding reproduces 31.1 exactly. FINDINGS 33. - a `scsi` window does not fit the 2 MB machine the rig emulates (2.84 MB of stream past a 0x200000 ceiling). The gate now verifies 80 of 120 frames and SAYS so, and fails loudly when the pass does not complete, instead of reporting a phantom 49,005-pixel diff. FINDINGS 36. Three near-misses this session had one shape: an unobservable run nearly produced a false finding. stdbuf -oL on any MAME job that prints progress -- a file is block-buffered too, and a run that is merely finishing looks exactly like one that is wedged. check.sh ALL GREEN. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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06b98d4b47 |
Price cycles in the mode decision: 37 misses become 1, for 0.26 dB
The decoder has been CPU-bound since FINDINGS 28 while the mode decision
minimised D + lam*R -- distortion against BYTES. decide() now minimises
D + lam*bytes + mu*cycles, and ratectl bisects mu per frame against the
833,333-cycle budget with the lam bisection nested inside it. On the worst
sustained window:
sasi 27.22 -> 26.95 dB, 109.5 -> 109.4 KB/s, 37/120 misses -> 1
scsi 29.90 -> 29.27 dB, 280.0 -> 278.6 KB/s, 51/120 misses -> 1
Bitrate does not move: the byte controller still binds, and mu changes WHICH
modes are bought. V4 is what it stops buying -- 25.2 -> 20.3% of blocks at sasi
and 15.0 -> 5.3% at scsi, where RAW takes it. That is 28.8's inversion in
practice: RAW is dearer in bytes and cheaper in cycles, so only the byte-rich
profile can buy its way out of V4.
Three things worth knowing beyond the headline:
- The one frame that still misses, at both profiles, is FRAME 0 -- no previous
reconstruction, so 100% changed by definition, which is also what a scene
cut is. It comes out at the all-V1 floor of 110.6% and is emitted late on
purpose. Freezing a cut to make a deadline is the worse failure.
- 28.7's "11 frames are impossible" was too pessimistic. That floor held the
SKIP set fixed and asked how cheaply the drawn blocks could be drawn; the
real decision can also MOVE a block to SKIP, which above ~90% non-SKIP is
the only lever left.
- SKIP's price depends on its neighbours (13.25 cycles clustered, 45 mixed),
which a per-block lagrangian cannot see. The way out is that the two uses
need not share a cost function: a ranking constant inside decide(), the
exact clustered rule for the frame-level bisection. vq_hybrid.cycles() is
now the one definition of that rule and 11_cpu_budget.py imports it.
Gated: 09_ratectl_drift.py runs both controllers, both 0/120 drifting frames.
The cost-aware container decodes pixel-exact on the 68000 (120 frames). ON by
default in encode.py; --no-cpu-fit restores session 7. check.sh ALL GREEN.
Still a model, not a measurement, for THIS container: FINDINGS 31's cycle
figures come from vq_hybrid.cycles (within 1 point of the 68000 on four frames
of the session-7 container). Timing this one on the machine is step 1 of the
next session -- it was started and killed for time, and it is slow.
FINDINGS 31. tools/analysis/13_cpu_ratectl.py.
Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6
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29eb78a599 |
Measure the span: the mode survives, and it is an encoder format
FINDINGS 29 priced a literal-span mode at 4*(50 + 4L*9.08) cycles and labelled
the whole section DERIVED. Session 8 step 0 was to measure it before optimising
over the mode set it implies. Two variants in blit.s, one stream per span length
from prep_spans.py, timed by span.lua, driven by span.sh in ~25 s:
v5, handed (x, npix) and left to work the copy out: 97.9/span + 10.459/px
v6, handed an address and a jump displacement: 43.7/span + 9.152/px
29 assumed 50.0/span + 9.080/px
So 29's arithmetic was right about a format nobody had written. The difference
is not tuning: v5 spends ~122 cycles a span computing a destination, dividing
npix into bursts and handling a 0..15 remainder, all of which the encoder knows
at build time. v6's record is {u32 absolute GVRAM address, u16 jump
displacement} into an unrolled chain of 24-pixel copy units -- no loop, no
remainder, no arithmetic -- and it fits 11 span lengths to 0.3%.
Three things that measurement showed and derivation could not:
- The per-pixel cost is a function of REGISTER PRESSURE. FINDINGS 24's 9.08
was a fixed blit with 12 registers free; v5 can spare 8 and pays 10.46; v6
gets 12 back only because the encoder holds the state.
- Short spans die in the remainder path -- a 12-pixel span costs MORE than a
16-pixel one -- and the fix is padding, not avoidance.
- Odd-x alignment is free (259.0 vs 261.8 cycles/span), as a 16-bit bus
implies but nobody had checked.
Re-priced against the unchanged mode maps, sasi: median 74.4% -> 52.0% (29 said
43.0), misses 37 -> 10/120 (29 said 8), 448.0 KB/s. Break-even moved from runs
of 2 blocks to runs of 4. 29.4 survives: a scene cut needs x >= 0.196 of the
frame as spans and the bus allows x <= 0.373, so it fits at 12fps.
All 23 timing configs are also checked pixel-exact, so none of this was timed
against a decoder that quietly skipped work.
FINDINGS 30. Next: lever B, the cost-aware mode decision.
Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6
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e1aa26bb57 |
The 68000 decoder draws pixel-exact frames, and does not fit
src/player/decode.s parses DLX1 and decodes straight into GVRAM. Verified pixel-exact over a 120-frame sequential run of the worst sustained window on the disc -- all four block modes, full temporal recursion, so the last frame is only right if all 120 were. In check.sh. It costs a mean of 81.7% of a 12fps frame budget, and 31% of frames exceed 100% (42% at scsi). CPU is now the binding constraint. FINDINGS 28. Three things that were believed and are not true: - The dual-display-path plan of FINDINGS 24.5/25.6 is incoherent. The compose path needs a RAM copy of the previous reconstruction; the direct path's selling point is that it keeps none. Mixing them shows stale pixels on 70 of 120 frames, worst frame 18.8% of the screen. Every coherent repair is dearer than not mixing, and 24.5's two figures were both copies with no decode in either, so there was never a crossover to find. One path ships, and the 96KB reference frame is gone. tools/analysis/10_pathmix_drift.py keeps the counterexample runnable; check.sh asserts it still reproduces. - The four block modes do not cost the same. V1 300, V4 448, RAW 400 cycles against the old model's flat 207.8. V4 is 25% of blocks and 50% of the cycles, and the mode decision charges it bytes it does not charge cycles for. tools/analysis/11_cpu_budget.py reproduces all four frames timed on the 68000 to within 1 point. Hand-derived timings agree to 0.5% on V1. - The container is big-endian but not aligned. Variable-length records laid end to end put frame 1's length field at an odd address, and move.l (a0)+ there is an address error: frame 0 decoded perfectly and then vectored into the IPL for 59 emulated seconds looking like a hang. Found by dumping PC, not by reading the source. Also: an all-V1 frame, the cheapest possible full redraw, is 110.5% of budget. No mode assignment fits a scene cut at 12fps. That one needs a decision, not a measurement. Next: charge cycles in the mode decision and bisect against 833,333 per frame, the way session 6 bisects lam against bytes -- but with no bucket, because a late frame cannot be banked. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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497f88b945 |
Rate control: rebuilt per-frame, wired in, and gated at zero drift
FINDINGS 26 stopped the session-5 rate controller before it shipped: it built a lam-ladder of independent whole-sequence encodes and picked frames off it, so SKIP blocks referenced reconstructions the decoder never saw -- 111 of 120 frames drifted. The fix is the structural one 26.1 said it had to be. vq_hybrid is now frame-drivable -- frame_ctx / decide / paint -- and encode() is a thin loop over it. Rate control drives the same three calls, bisects lam per frame under the leaky bucket, and feeds back the frame it actually emitted. The desync has no way to occur, and 09_ratectl_drift.py goes 111/120 -> 0/120. That test is now part of check.sh, which is ~2 min rather than ~40 s. Both overshoots on the worst sustained window are closed for under 1 dB, totals including audio: sasi 137.4 -> 109.5 KB/s (-0.60 dB), scsi 381.6 -> 280.0 KB/s (-0.91 dB). Zero frames hit the lam=800 cliff, so nothing was destroyed to get there. Rate control also makes the display path cheaper -- scsi's median drops 53.6% -> 47.1% -- because raising lam moves blocks to SKIP and V1. Two knobs measured rather than guessed. --rc-floor is worth 0.00 dB on that window and defaults to the profile lam, so rate control cannot regress content that already fits. --prefill defaults to 0 and is documented as a trap: it buys a permission to overshoot of exactly bucket/nframes, and on a 14-frame clip it disables the controller outright. FINDINGS 26.5 was wrong in both halves and 27.6 records it. _paint was not the bottleneck (14% of a frame, though vectorising it was still right at 17.1x) and the ladder was never "minutes" -- those were k-means in build(). What makes per-frame rate control affordable is that VQ.assign depends on neither lam nor prev, so it is cached one frame deep: a 12-step search over 120 frames costs 0.31 s against 49.1 s. Also caught: fixed-lam sasi was already 5% over target on 00020, the clip everyone called easy. Nothing noticed because the profile table quotes PSNR and not bitrate. check.sh: ALL GREEN. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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145753c0bf |
Handoff: rate control is next, and it is unsound as written
Session 5 handoff. The user has chosen rate control as the next session's work, so this reads ratectl.py properly before that session starts rather than discovering the problem mid-implementation. FINDINGS 26: encode_rate_controlled() is not sound. H.encode() is temporally recursive -- SKIP blocks copy the previous RECONSTRUCTION -- but rate control builds a ladder of independent whole-sequence encodes and picks each frame from whichever rung fits the budget. Frames then reference reconstructions the decoder never saw. Measured on the Singe window: 67 rung switches, 111 of 120 frames drift, worst frame 43.4% of pixels, reported PSNR overstated by 0.36 dB. It would have wired up cleanly and reported a plausible wrong answer. Two further defects in the same function: the lam ladder runs to 2e5, 250x past the FINDINGS 15 cliff, so a frame that only fits up there is destroyed rather than rate-controlled; and with 5 rungs only two are ever chosen, straddling the operating point by 7.5x. The docstring describes a per-frame binary search, which is the right design -- the implementation is a fixed ladder. The leaky bucket does work and should be kept: 109.1 KB/s against a 110 target. tools/analysis/09_ratectl_drift.py is the regression test and the acceptance criterion: it exits non-zero until zero frames drift. Also corrected the stale 38% blit figure in ratectl.py's profile commentary, which session 5 measured at 53.6% (FINDINGS 24), and recorded the pgrep -f self-kill trap again -- four times across three sessions now. check.sh ALL GREEN. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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e00264a058 |
Find the sustained action sequence: it breaks both profiles
The open risk since session 2 was "a sustained action sequence could still break the bitrate", with every clip measured so far being 1.2-1.7 s. Closed by measurement rather than by sampling clips by hand. 07_motion_survey.py scans a whole stream at 96x72 for the hottest sliding window of inter-frame difference. On 00223 the spread between the quietest and hottest sustained 10 s windows is 10.6x, which is the argument for not eyeballing it. Hottest is t=539.4s, the Singe endgame. There, with the fixed lam the CLI uses, sasi overshoots 110 -> 129.6 KB/s (+18%) and scsi 280 -> 373.8 KB/s (+34%). Rate control moves from "insurance, not a fix" to required, and is promoted above the full-disc survey. The bus is not broken -- 381.6 KB/s still fits the 488 KB/s figure -- so FINDINGS 21 survives, at 78% of the pipe instead of a comfortable margin. Three further corrections fall out: - The two largest streams on the disc are bonus material. 00216 is the feature with a burned-in commentary PiP; 00215 is the commentary. 00223 is the clean 9.4 min. A size-ranked survey would have encoded live action. - On hard content the 256-colour scene palette (31.33 dB) binds well before the X68000 display (40.81 dB); scsi is already within 0.51 dB of it. - FINDINGS 24.5's architecture question resolves to "both paths, chosen per frame": 30-53% of frames sit above the 70% crossover. Picking per frame costs a median 37.0% of the frame budget and caps at 53.6%. Reporting for this is wired into encode.py, which previously only printed a mean over all frames -- the one statistic that cannot answer a per-frame question. extract.py takes optional start/dur; 08_mode_map.py renders source | decoded | block-mode map to .webm. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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7ba979a236 |
Handoff: green-light script, reconciled figures, a smaller first step for the decoder
Prepares session 4 for handoff. No new measurements; this reconciles the docs with what session 4 changed and makes the next session's entry point cheaper. - tools/bench/check.sh re-runs both display regression tests from the Blu-ray in ~40 s and prints ALL GREEN. Verified green cold, after wiping tmp/ and re-extracting. STATUS and README both open with it, because everything downstream assumes the display path is pixel-exact and nothing previously checked that in one command. - Reconciled the figures session 4 invalidated. Session 3's 38.88 dB ceiling is struck through in STATUS with a pointer to 40.81; the "three facts the player must honour" table no longer quotes R20 = 0x0116, which was the 768-wide IPL timing and would have been copied into the player as if it were the shipping value. crtc_mode.lua is now named as the single source of truth for CRTC registers, in both STATUS and README. The 38.88 dB in the session-3 reproduce section is left alone and annotated instead: it is correct for that test, which still packs I = 1. The two numbers disagree for a reason and a reader should be able to see which is which. - Next-step 2 now leads with something smaller than "write the decoder": a dumb full-frame RAM->GVRAM blit in 68000 code, timed. That number alone confirms or kills the 38% estimate, and needs no bitstream, codebooks, or DLX1 parsing. The reference image and its checker already exist. - Parked the user's Cliff Hanger / Lupin III follow-on in STATUS so it is not lost and not mistaken for scheduled work. Cheaper than this project on every axis except media prep, which is where it would actually stall. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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64cd1ffd72 |
Handoff: reconcile docs and tooling with the corrections made this session
Session 2 reversed several of its own conclusions. The docs are append-only, so a reader could land on a superseded section and act on it. This pass makes the repo internally consistent. Defects found and fixed in STATUS.md: - claimed "Hybrid VQ with k=1024: no" as the answer to the linework question, directly contradicting FINDINGS 14, which rejected k=1024. Both profiles are k=256. - malformed profile table (six column separators, five columns). - next-steps list had two items numbered 3 and listed the full-disc survey twice. - the disk-benchmark section still read CRITICAL-PATH with "if SCSI sustains >=800 KB/s, ship pixel-exact". That was written while the bandwidth figure was misread as 4 MB/s. At 4 Mbps pixel-exact needs 92-97% of the pipe and is not available, and the ring-buffer result means the design no longer hangs on the benchmark at all. Rewritten with what it IS still worth doing: confirming the 4 Mbps provenance, and confirming DMA is used rather than PIO. FINDINGS now carries supersession blockquotes on 5, 8, 11, 17 and 18 pointing at the sections that correct them. 18 is the dangerous one -- its peak-vs- sustained test is reversed by 21 -- so it is marked DO NOT ACT ON THIS SECTION while noting the per-frame data itself remains valid. profile_gen.py had the same problem in code: it defaulted to the superseded peak sizing and returned lam=25 where the docs say lam=10. The buffered test is now the default and peak sizing is behind --size-for-peak as a bound only. A tool that contradicts the findings is worse than no tool. Also preserves the five measurement scripts that produced this session's numbers as tools/analysis/05-09, following the session 1 precedent, and adds an "explicitly abandoned -- do not re-propose" list to STATUS covering entropy coding, k=1024 codebooks and flat 4x4 VQ. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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e4062ed294 |
Session 2: hybrid VQ codec, two quality profiles, three corrections
Answers session 1's critical-path question. Flat 4x4 VQ at k=256 was prototyped and REJECTED by eye: Dirk's face disintegrates and ink outlines break into 4-pixel stair-steps. The 256-colour palettised frame is excellent, so the palette was never the problem -- block VQ was. Replaced it with a Cinepak-style hybrid: each 4x4 block is SKIP, one 4x4 codeword, four 2x2 codewords, or RAW literal pixels, chosen per block by rate-distortion. The RAW escape makes lam=0 pixel-exact (measured 0.00 dB loss), so the quality knob spans lossless to heavily-compressed in one bitstream. Per the user's decision, ships TWO quality profiles from that one codec, one decoder and one bitstream -- only the rate knob differs: sasi 45 KB/s lam=300 34.8 dB stock 10MHz ACE/EXPERT scsi 75 KB/s lam=100 35.9 dB Super/XVI or CZ-6BS1 Three corrections to earlier numbers: 1. Session 1's "183 KB/s at 12fps" was a bad extrapolation. Halving the framerate does not halve the bitrate -- decimation roughly doubles the per-frame delta. Re-measured directly: 340 KB/s for session 1's own RLE, 247 KB/s for changed-spans+deflate. The lossless floor is 319 MB. 2. A FOURTH false-good result, same family as the three in FINDINGS 4: k=1024 codebooks appeared to buy +2.4 dB free, because the rate model charged 1 byte for a 10-bit index. Charging the true cost reverses the verdict -- k=256 wins at every matched bitrate, and by 5 dB at the low end where the SASI profile lives. k=256 ships. 3. Stream inventory: the ~3-5MB clips are 1.2-1.7s, not ~60s, and some 60s streams are menus, not content. Any survey must classify before averaging. Also cleared both candidate sources for the game-logic layer: the SNES project is MIT and DirkSimple is zlib, so the arcade scene graph can be imported and the two transcriptions diffed against each other. Encoder is working end-to-end: extract.py -> vq/vq_hybrid/ratectl -> encode.py, emitting a big-endian DLX1 container the 68000 can parse with plain moves. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |
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65112b9305 |
Session 1: hardware research, content measurement, codec decision, MAME harness
Verified GVRAM is one word-access per pixel in ALL color modes; chose 256-color 256x192 with movem.l bursts (page 1 sacrificed as double-buffer). Measured 8 scenes from the Blu-ray source: blit costs under 8% of the 12fps cycle budget, so I/O is the bottleneck, not CPU. Naive delta+RLE reaches only 3.2:1 (365 KB/s, 470MB) -> decision to use 4x4 vector quantization (~30 KB/s). "Shot on twos" assumption failed: the transfer has zero duplicate frames, so 12fps requires explicit decimation. Documents three false measurement results and their root causes (per-frame Floyd-Steinberg dithering, temporal denoise, exact-match dedupe on noisy source). MAME Lua injection harness works and is reusable for cycle-cost measurement; the IOCS _B_READ disk benchmark is blocked returning -1. Claude-Session: https://claude.ai/code/session_01194oWYW8DQXK1SZ2DnChW6 |