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WP40 RAID: Phase 3 gate — primitives benchmark records, summary, figure; status/progress updated

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Simon-Pierre Boucher committed (Nov 2, 2026) parent 5aa6672 Browse files

8 changed files +5,287 −8

modified RESEARCH_STATUS.md +7 −8
@@ -1,6 +1,6 @@
1 1 # RESEARCH_STATUS.md — RAID (UQO WP 40)
2 2
3 −Last update: 2026-11-02 (Phase 2 passed). Legend: ✅ verified by tests/artifacts · 🧪 implemented, validation pending ·
3 +Last update: 2026-11-02 (Phase 3 passed). Legend: ✅ verified by tests/artifacts · 🧪 implemented, validation pending ·
4 4 🧭 experimental · ⛔ blocked · ⏳ planned · ✖ not implemented (deliberately).
5 5
6 6 ## Phases
@@ -9,7 +9,7 @@ Last update: 2026-11-02 (Phase 2 passed). Legend: ✅ verified by tests/artifact
9 9 | 0 Audit | scope & feasibility memo | ✅ passed 2026-11-02 | `docs/audit.md`, `docs/capabilities.md`, `docs/novelty_matrix.md`, `docs/risks.md`, `docs/PROGRESS.md` |
10 10 | 1 Foundation | clean build + tests + docs | ✅ passed 2026-11-02 | `ctest` 26/26 (314 assertions), `pytest` 7/7, `docs/PROGRESS.md` Phase 1 |
11 11 | 2 Data | offline synthetic tests + opt-in live tests | ✅ passed 2026-11-02 | offline `[findata]` 4/4, live `[live]` 2/2 (60 assertions), `docs/operations/findata.md` |
12 −| 3 Numerical primitives | accuracy + measured break-even | ⏳ | — |
12 +| 3 Numerical primitives | accuracy + measured break-even | ✅ passed 2026-11-02 | `[metal]` 6 cases / 6 411 assertions; `experiments/results/bench_primitives_summary.json` (Metal wins: fused realized ≥ 39 k elements up to 3.4×, GARCH NLL P=64 up to 7.9×; CPU wins: rolling sums, GARCH P=1, small panels) |
13 13 | 4 Econometrics (Tier A) | references + Monte Carlo | ⏳ | — |
14 14 | 5 Extensions (Tier B) | per-feature specs + tests | ⏳ | — |
15 15 | 6 Benchmarking E1–E7 | every claim traceable | ⏳ | — |
@@ -20,10 +20,10 @@ Last update: 2026-11-02 (Phase 2 passed). Legend: ✅ verified by tests/artifact
20 20 | Method | Tier | CPU FP64 | Metal FP32 | Reference software | Status |
21 21 |---|---|---|---|---|---|
22 22 | returns (log/arith), lag/lead, rolling windows, calendar-aware aggregation | A | ✅ | ⏳ (Phase 3) | numpy; exchange_calendars (calendar exact 2000–2026) | ✅ CPU |
23 −| RV, BPV, RSV±, RQ, jump proxy, TriPV, rCov/rCorr | A | ✅ (numpy truth 1e−12) | ⏳ (Phase 3) | highfrequency 1.0.3 (R comparison Phase 4) | ✅ CPU |
24 −| OLS/WLS/ridge, HC0–3, HAC, cluster, rolling OLS | A | ✅ (statsmodels 1e−9) | ⏳ (sufficient stats, Phase 3) | statsmodels 0.15, scipy 1.18 | ✅ CPU |
23 +| RV, BPV, RSV±, RQ, jump proxy, TriPV, rCov/rCorr | A | ✅ (numpy truth 1e−12) | ✅ fused kernel 1e−6 vs FP64 | highfrequency 1.0.3 (R comparison Phase 4) | ✅ CPU |
24 +| OLS/WLS/ridge, HC0–3, HAC, cluster, rolling OLS | A | ✅ (statsmodels 1e−9) | ✅ sufficient statistics 1e−6 (k ≤ 8) | statsmodels 0.15, scipy 1.18 | ✅ CPU |
25 25 | HAR-RV, log-HAR, HAR-X, HARQ | A | ⏳ | ⏳ | highfrequency `HARmodel`, statsmodels | ⏳ |
26 −| GARCH(1,1), GJR, EGARCH (N, t), QMLE/Hessian/OPG SE, forecasts | A | ✅ (arch 8.0: loglik 5e−4, params 5 %) | ⏳ (batched likelihood, Phase 3) | arch 8.0 ✅, rugarch 1.5.6 (Phase 4) | ✅ CPU |
26 +| GARCH(1,1), GJR, EGARCH (N, t), QMLE/Hessian/OPG SE, forecasts | A | ✅ (arch 8.0: loglik 5e−4, params 5 %) | ✅ batched NLL 2e−5 (grids) | arch 8.0 ✅, rugarch 1.5.6 (Phase 4) | ✅ CPU |
27 27 | Bootstrap (stationary / circular block), Monte Carlo | A | ⏳ | ⏳ | arch.bootstrap | ⏳ |
28 28 | VAR, GFEVD, Diebold–Yilmaz | B | ⏳ | ⏳ | statsmodels VAR | ⏳ |
29 29 | Realized GARCH, HEAVY, DCC, PCA/shrinkage, Kalman | B | ✖ until Tier A passes | | | ⏳ |
@@ -35,6 +35,5 @@ Last update: 2026-11-02 (Phase 2 passed). Legend: ✅ verified by tests/artifact
35 35 not tested unless they come back.
36 36
37 37 ## Next safe action
38 −Phase 3: Metal backend (device discovery, runtime + prebuilt shader library, buffer pool, batched reductions,
39 −rolling sums, regression sufficient statistics, GARCH likelihood batch), FP32-vs-FP64 accuracy tests, first break-even
40 −microbenchmarks (bench_reductions) with manifests.
38 +Phase 4: HAR family (fit, rolling, batched via GPU sufficient statistics), block bootstrap, R references
39 +(highfrequency / rugarch), Monte Carlo (bias/RMSE/coverage), gradient checks, registry completion.
modified docs/PROGRESS.md +39 −0
@@ -81,3 +81,42 @@ Executed:
81 81
82 82 Gate evidence: offline tests in `ctest`; live run transcript above; no vendor data in git (`scripts/check_no_secrets.sh`).
83 83 Open: least-privilege key for benchmarks (needs `findata create-key` on M3U96a — owner action, optional).
84 +
85 +## Phase 3 — Numerical primitives (2026-11-02, 15:40–16:30 ET) — GATE PASSED
86 +Plan: Metal backend with FP32 "double-float" (error-free-transform) accumulation, fused realized kernel, rolling sums,
87 +regression sufficient statistics, batched GARCH likelihood; CPU/GPU agreement tests; measured break-even analysis.
88 +
89 +Executed:
90 +- `backends/metal/shaders/raid_kernels.metal` (TwoSum/Fast2Sum double-float, deterministic threadgroup tree reductions,
91 + chunked partial sums combined in FP64 on the CPU) and `backends/metal/host/metal_backend.mm` (device discovery,
92 + prebuilt `raid.metallib` with runtime-MSL fallback, pipeline cache, buffer pool by power-of-two size class, GPU
93 + timing from `GPUStartTime/GPUEndTime`, `-fno-fast-math` / `fastMathEnabled = NO` so the compensation is not optimised
94 + away). Metal has no `lgamma`/`log1p`: Student-t constants are computed in FP64 on the host and passed per parameter
95 + vector.
96 +- Tests `[metal]` (6 cases, 6 411 assertions): fused and single-statistic accumulators vs CPU FP64 within 1e−6
97 + (Σx⁴ 1e−5) for n = 390/3 900/39 000 across chunk boundaries (4 096); bitwise determinism across runs; rolling sums
98 + 1e−5; regression statistics 1e−6 (and the solve from GPU statistics agrees with CPU QR to 1e−5); batched GARCH NLL
99 + 2e−5 relative (GJR + Student-t fixed ν 5e−5), argmin over a 16-point grid identical; +inf on invalid parameters.
100 + Full suite: `ctest` 38/38 (2 live skipped), `pytest` 7/7.
101 +- `bench_bench_primitives` (laptop M5 Max 40-core GPU, 18 CPU threads, load ≈ 3–4 from other sessions, no thermal
102 + warning, 5 repetitions, shuffled order, 2 warm-ups; raw records `experiments/results/raw/bench_primitives.jsonl`
103 + + manifest; summary `experiments/results/bench_primitives_summary.{json,csv}`, figure
104 + `fig_bench_primitives_throughput.pdf`). Medians of wall-clock including FP64→FP32 conversion and buffer traffic;
105 + verdicts use non-overlapping bootstrap 95 % CIs of the median:
106 + - realized_fused: Metal wins from 39 000 elements (100 × 390: 2.4×), 2.0–3.4× vs 18-thread CPU at 3.9 M–39 M
107 + elements (max 3.4× at 1 000 × 39 000); ties at 390 000 for 10 × 39 000 and 100 × 3 900 shapes; CPU 1 thread is
108 + 27–40× slower than Metal at 39 M.
109 + - regression_stats (k = 4): break-even ≈ 390 000 elements for a single long series (3.9×); ties for most shapes
110 + between 390 k and 3.9 M; 1.1–1.4× at 39 M. CPU wins below 39 000 elements.
111 + - rolling_sumsq (w = 22, direct O(w) kernel): **CPU wins at every size** (Metal 0.4–0.9× of CPU-MT); the GPU kernel
112 + is memory/arithmetic-bound by its O(w) design and the CPU running sum is O(1) per element — a negative result kept
113 + for the paper (a scan-based kernel is future work).
114 + - garch_nll: with one parameter vector per series (P = 1) the **CPU wins everywhere** (0.01–0.33×; the recursion is
115 + sequential and the GPU is launch-bound); with P = 64 parameter vectors per series Metal wins from 100 series
116 + (1.9×) up to 7.9× at 1 000 × 3 900 — batched likelihood evaluation is where the GPU pays off.
117 + - Device time is 5–20× smaller than wall time for the reductions: FP64→FP32 conversion and buffer fills dominate
118 + ("unified memory is not free computation"); E6 will add the FP32-resident ablation.
119 + - Shader library: prebuilt metallib loaded in 0.23 ms; first kernel call 14 ms (pipeline creation); runtime MSL
120 + compilation of the bundle is measured separately in E7 (toolchain-less nodes).
121 +
122 +Gate evidence: accuracy tests and the measured break-even table above; no claim beyond the tested shapes.
added experiments/results/bench_primitives_summary.csv +208 −0
@@ -0,0 +1,208 @@
1 +kernel,S,n,elements,backend,threads,median_s,ci_lo,ci_hi,device_s,elements_per_s,reps,precision,peak_rss_mb
2 +garch_nll_P1,1,390,390,cpu,1,1.7909333109855652e-06,1.7499551177024841e-06,1.8328428268432617e-06,0.0,217763552.44929796,5,fp64,3255.451648
3 +garch_nll_P1,1,390,390,cpu,18,1.7499551177024841e-06,1.6670674085617065e-06,1.8333084881305695e-06,0.0,222862858.62692922,5,fp64,3368.943616
4 +garch_nll_P1,1,390,390,metal,0,0.0009180000051856041,0.00044724997133016586,0.0009358339011669159,0.00032679166179150343,424836.59890736995,5,fp32,2962.440192
5 +garch_nll_P1,1,3900,3900,cpu,1,1.6250181943178177e-05,1.6207806766033173e-05,1.637497916817665e-05,0.0,239997312.86930108,5,fp64,2962.440192
6 +garch_nll_P1,1,3900,3900,cpu,18,1.695798709988594e-05,1.691700890660286e-05,1.9416213035583496e-05,0.0,229980125.41395503,5,fp64,3431.858176
7 +garch_nll_P1,1,3900,3900,metal,0,0.001348957885056734,0.0010095001198351383,0.0015331669710576534,0.0011987084290012717,2891120.6518771155,5,fp32,2962.440192
8 +garch_nll_P1,10,390,3900,cpu,1,2.1916814148426056e-05,2.1541956812143326e-05,7.208297029137611e-05,0.0,177945570.62847915,5,fp64,2962.440192
9 +garch_nll_P1,10,390,3900,cpu,18,2.929195761680603e-05,1.7000362277030945e-05,4.200031980872154e-05,0.0,133142347.50095384,5,fp64,2962.440192
10 +garch_nll_P1,10,390,3900,metal,0,0.0003432091325521469,0.0003193751908838749,0.0009956671856343746,0.00019762502051889896,11363333.98531415,5,fp32,2920.169472
11 +garch_nll_P1,10,3900,39000,cpu,1,0.0002155420370399952,0.00016279099509119987,0.00037720799446105957,0.0,180939182.60948467,5,fp64,576.782336
12 +garch_nll_P1,10,3900,39000,cpu,18,6.916606798768044e-05,6.245775148272514e-05,7.533328607678413e-05,0.0,563860302.2358668,5,fp64,781.43488
13 +garch_nll_P1,10,3900,39000,metal,0,0.0014300826005637646,0.0012115412391722202,0.0016847080551087856,0.0010766249615699053,27271152.019208886,5,fp32,3360.11264
14 +garch_nll_P1,100,390,39000,cpu,1,0.0001916671171784401,0.0001916252076625824,0.0002199173904955387,0.0,203477782.59580857,5,fp64,3431.87456
15 +garch_nll_P1,100,390,39000,cpu,18,0.00016116676852107048,0.00015066703781485558,0.00017320923507213593,0.0,241985369.30335766,5,fp64,3359.932416
16 +garch_nll_P1,100,390,39000,metal,0,0.0006238752976059914,0.0006115422584116459,0.0006384579464793205,0.0004310833755880594,62512492.720348835,5,fp32,3355.901952
17 +garch_nll_P1,100,3900,390000,cpu,1,0.0016154590994119644,0.0016071251593530178,0.0016200002282857895,0.0,241417439.87326083,5,fp64,3222.339584
18 +garch_nll_P1,100,3900,390000,cpu,18,0.00020695803686976433,0.00020262505859136581,0.0002222089096903801,0.0,1884439985.5098226,5,fp64,2962.440192
19 +garch_nll_P1,100,3900,390000,metal,0,0.0016493331640958786,0.0015722080133855343,0.004429208114743233,0.0009533748961985111,236459199.68740082,5,fp32,2962.440192
20 +garch_nll_P1,1000,390,390000,cpu,1,0.0016390001401305199,0.001627500168979168,0.0016581248492002487,0.0,237949949.14945084,5,fp64,3359.932416
21 +garch_nll_P1,1000,390,390000,cpu,18,0.0002765827812254429,0.00027295900508761406,0.00033191684633493423,0.0,1410066086.8042636,5,fp64,2962.440192
22 +garch_nll_P1,1000,390,390000,metal,0,0.0011531668715178967,0.0010962923988699913,0.0011774590238928795,0.00017799995839595795,338199101.65009224,5,fp32,3222.339584
23 +garch_nll_P1,1000,3900,3900000,cpu,1,0.018310166895389557,0.01771716633811593,0.019527375232428312,0.0,212996420.09172553,5,fp64,572.112896
24 +garch_nll_P1,1000,3900,3900000,cpu,18,0.0014978330582380295,0.001383374910801649,0.0015932917594909668,0.0,2603761466.306366,5,fp64,3432.742912
25 +garch_nll_P1,1000,3900,3900000,metal,0,0.0072068748995661736,0.007158916909247637,0.009398084133863449,0.0010924999369308352,541149951.171591,5,fp32,3360.11264
26 +garch_nll_P1,10000,390,3900000,cpu,1,0.017741417046636343,0.01734916679561138,0.017816499806940556,0.0,219824605.3146817,5,fp64,3355.901952
27 +garch_nll_P1,10000,390,3900000,cpu,18,0.0022433330304920673,0.002103041857481003,0.002292540855705738,0.0,1738484632.905596,5,fp64,2962.440192
28 +garch_nll_P1,10000,390,3900000,metal,0,0.00675466563552618,0.006540417205542326,0.007071124855428934,0.00046787504106760025,577378690.5880197,5,fp32,2962.440192
29 +garch_nll_P1,10000,3900,39000000,cpu,1,0.16226391727104783,0.16133012529462576,0.16484179068356752,0.0,240349183.3298581,5,fp64,3255.451648
30 +garch_nll_P1,10000,3900,39000000,cpu,18,0.01383341709151864,0.012941500172019005,0.014138792175799608,0.0,2819260038.3538756,5,fp64,3254.272
31 +garch_nll_P1,10000,3900,39000000,metal,0,0.06106641702353954,0.05950908316299319,0.0616582497023046,0.004054000019095838,638648899.0334327,5,fp32,3355.901952
32 +garch_nll_P64,1,390,390,cpu,1,8.287513628602028e-05,8.27503390610218e-05,8.458364754915237e-05,0.0,4705874.614239238,5,fp64,577.159168
33 +garch_nll_P64,1,390,390,cpu,18,0.00017224997282028198,0.00012754183262586594,0.0002139592543244362,0.0,2264151.3006617934,5,fp64,3431.514112
34 +garch_nll_P64,1,390,390,metal,0,0.0005012080073356628,0.00047737499698996544,0.0006123748607933521,0.0003255000337958336,778120.0505418383,5,fp32,3431.46496
35 +garch_nll_P64,1,3900,3900,cpu,1,0.0008078329265117645,0.0008031250908970833,0.0008203750476241112,0.0,4827730.923076213,5,fp64,3431.87456
36 +garch_nll_P64,1,3900,3900,cpu,18,0.00014187488704919815,0.000135000329464674,0.00021779071539640427,0.0,27489008.668937948,5,fp64,3222.339584
37 +garch_nll_P64,1,3900,3900,metal,0,0.0014235423877835274,0.00134983379393816,0.0033927499316632748,0.00122337497305125,2739644.4485733556,5,fp32,3431.87456
38 +garch_nll_P64,10,390,3900,cpu,1,0.0008257082663476467,0.000809917226433754,0.0008320827037096024,0.0,4723217.8227436915,5,fp64,3432.742912
39 +garch_nll_P64,10,390,3900,cpu,18,0.0002438751980662346,0.00013074977323412895,0.0002598753198981285,0.0,15991786.089460358,5,fp64,3368.943616
40 +garch_nll_P64,10,390,3900,metal,0,0.0010179998353123665,0.0004632081836462021,0.0010751672089099884,0.00032300001475960016,3831041.877136759,5,fp32,3431.530496
41 +garch_nll_P64,10,3900,39000,cpu,1,0.008083874825388193,0.008056249935179949,0.00812424998730421,0.0,4824419.086440666,5,fp64,3355.901952
42 +garch_nll_P64,10,3900,39000,cpu,18,0.000775500200688839,0.0006874999962747097,0.0008766250684857368,0.0,50290122.38211957,5,fp64,3432.742912
43 +garch_nll_P64,10,3900,39000,metal,0,0.0013822498731315136,0.0008970410563051701,0.0033571659587323666,0.0006641249638050795,28214869.654243305,5,fp32,3431.530496
44 +garch_nll_P64,100,390,39000,cpu,1,0.008346542250365019,0.008285791147500277,0.008543540723621845,0.0,4672593.611839012,5,fp64,3431.514112
45 +garch_nll_P64,100,390,39000,cpu,18,0.001005750149488449,0.0009415419772267342,0.0010966667905449867,0.0,38777026.30204572,5,fp64,781.484032
46 +garch_nll_P64,100,390,39000,metal,0,0.0005332920700311661,0.0005230000242590904,0.0005429168231785297,0.00033650000113993883,73130658.02332444,5,fp32,2962.440192
47 +garch_nll_P64,100,3900,390000,cpu,1,0.0801338329911232,0.07999316696077585,0.08033083425834775,0.0,4866858.172667244,5,fp64,3359.932416
48 +garch_nll_P64,100,3900,390000,cpu,18,0.006173874717205763,0.005890249740332365,0.006268457975238562,0.0,63169406.22606451,5,fp64,3432.742912
49 +garch_nll_P64,100,3900,390000,metal,0,0.0021704169921576977,0.0018634586594998837,0.0022297906689345837,0.0010580417001619935,179688972.86059555,5,fp32,3431.858176
50 +garch_nll_P64,1000,390,390000,cpu,1,0.09679854195564985,0.08949454175308347,0.10223195794969797,0.0,4028986.306205791,5,fp64,2962.440192
51 +garch_nll_P64,1000,390,390000,cpu,18,0.00848708301782608,0.008417499717324972,0.008939292281866074,0.0,45952183.94598623,5,fp64,2962.440192
52 +garch_nll_P64,1000,390,390000,metal,0,0.002336665987968445,0.002312499564141035,0.0027117920108139515,0.001452916651032865,166904470.73228282,5,fp32,3359.932416
53 +garch_nll_P64,1000,3900,3900000,cpu,1,0.8561791670508683,0.8505779169499874,0.9446879159659147,0.0,4555121.34619399,5,fp64,2962.440192
54 +garch_nll_P64,1000,3900,3900000,cpu,18,0.08150566695258021,0.0744811249896884,0.10778554202988744,0.0,47849433.61384933,5,fp64,3255.451648
55 +garch_nll_P64,1000,3900,3900000,metal,0,0.010272707790136337,0.009604125283658504,0.010956583078950644,0.0029698750004172325,379646737.7125929,5,fp32,2962.440192
56 +realized_fused,1,390,390,cpu,1,1.4998950064182281e-06,1.416075974702835e-06,4.041939973831177e-06,0.0,260018200.16144055,5,fp64,2962.440192
57 +realized_fused,1,390,390,cpu,18,1.4998950064182281e-06,1.4579854905605316e-06,1.6670674085617065e-06,0.0,260018200.16144055,5,fp64,2962.440192
58 +realized_fused,1,390,390,metal,0,0.0002344171516597271,0.00019499985501170158,0.00025337468832731247,3.199989441782236e-05,1663700.7882687368,5,fp32,3432.742912
59 +realized_fused,1,3900,3900,cpu,1,1.1624768376350403e-05,1.1375173926353455e-05,1.2792181223630905e-05,0.0,335490555.4879026,5,fp64,2962.440192
60 +realized_fused,1,3900,3900,cpu,18,1.116609200835228e-05,1.1124648153781891e-05,1.2124888598918915e-05,0.0,349271705.5423496,5,fp64,3432.742912
61 +realized_fused,1,3900,3900,metal,0,0.0006333747878670692,0.0001420830376446247,0.000777125358581543,2.037500962615013e-05,6157491.7011356,5,fp32,2913.878016
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