Add bounded ZeroGPU portability receipts
Browse files
MANIFEST.sha256
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9ba9550ad48438d0836ddab3da480b3b69ffa0aac7b7878b5a0039e7ab429411 ./LICENSE
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-
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452cc3ee4dc29b0fe32e2c4dc128f10b44bf656009034f69cf9e6e9af4a2912f ./evidence/batching/receipt.json
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8b24a8b48d6c92b0a15626fa29648e004fa3a6683b1259f450d237a16d52c201 ./evidence/continuation/replay-summary.json
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a544bc63406cce60422217c98cc72a7ac0a6182fe898feba081faa2d4ec51283 ./evidence/continuation/top64-seed-transfer-summary.json
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4111844b1073916e590918c5d031ad52a39ecd3aa9c9fcec86c81063bf8e3fe6 ./evidence/horizon/matched-runtime-reproduction.json
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1abd6ee64e1d1122a17aa9b83a6905dbd638be998c29de88a322bb9f6bf43229 ./evidence/horizon/measurements.json
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c27b5c3102701624b260a4067b991454119193b6bd292fe476f0cff246e31ef5 ./evidence/keyframe/measurements.json
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c04848664bbb61970b2f3a83ba390890a08022a6e90c6b64ecb82c491e3a8136 ./evidence/mnist/REPRODUCTION_RECEIPT.md
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9ba9550ad48438d0836ddab3da480b3b69ffa0aac7b7878b5a0039e7ab429411 ./LICENSE
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a544bc63406cce60422217c98cc72a7ac0a6182fe898feba081faa2d4ec51283 ./evidence/continuation/top64-seed-transfer-summary.json
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f819356aa1d25c9e306c1e91411c7c3a54377db42e516ead31aeaf786b5aece9 ./evidence/horizon/zerogpu-portability/local-cpu-measurements.json
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3039fc2eff20441d3d19035b135892312456b22a19aec3d7fc62028c74cf1dbb ./evidence/horizon/zerogpu-portability/local-cpu-run-receipt.json
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656bb83621c6f9695f8c4041b3743439f325351bb01da7dd0f0fefee2070171f ./evidence/horizon/zerogpu-portability/zerogpu-receipt.json
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ea0e76a72e499d5fd5a6f0e3d5598da5e96db8dbc9c27d5994d4aaf6fea183c4 ./evidence/keyframe/original-verification.json
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c04848664bbb61970b2f3a83ba390890a08022a6e90c6b64ecb82c491e3a8136 ./evidence/mnist/REPRODUCTION_RECEIPT.md
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README.md
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@@ -27,6 +27,12 @@ The long-horizon evidence includes a matched-runtime reproduction receipt for
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the exact PyTorch 2.13 result through 8,192 transitions and separately records
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the observed PyTorch 2.8 strict-hash portability boundary.
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## License
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Original Dataset material is licensed under the Creative Commons Attribution
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@@ -43,4 +49,5 @@ are not relicensed by this Dataset.
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itself. The final HF Space must pin an exact Dataset commit rather than follow
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the mutable `main` branch.
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-
Status:
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the exact PyTorch 2.13 result through 8,192 transitions and separately records
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the observed PyTorch 2.8 strict-hash portability boundary.
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`evidence/horizon/zerogpu-portability/` adds a bounded three-horizon control
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comparing the local PyTorch 2.13 CPU path with a PyTorch 2.13 CUDA run on
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Hugging Face ZeroGPU. Every recorded scientific decision agreed; blanket
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numerical identity did not. The control is neither a full 8,192-transition
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reproduction nor a CPU-versus-GPU performance benchmark.
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## License
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Original Dataset material is licensed under the Creative Commons Attribution
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itself. The final HF Space must pin an exact Dataset commit rather than follow
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the mutable `main` branch.
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Status: public evidence Dataset. Publishing the Community Article remains a
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separate final gate.
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evidence/horizon/zerogpu-portability/README.md
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# Bounded ZeroGPU portability control
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This directory records a three-horizon portability control at horizons 32, 64,
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and 128. It compares the local CPU authority path with a Hugging Face ZeroGPU
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CUDA execution using the same hash-bound checkpoint and PyTorch 2.13 family.
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Files:
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- `local-cpu-run-receipt.json` records the complete local CPU authority run,
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including the exact result through horizon 8,192 and observed resource use.
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- `local-cpu-measurements.json` contains that run's machine-readable
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measurements.
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- `zerogpu-receipt.json` records the bounded CUDA environment, comparisons,
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numerical deltas, and interpretation.
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All decision-bearing comparisons agreed for the three tested horizons. The
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complete arrays were not blanket-identical: the largest absolute difference
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was approximately 0.00070273 in a third-order final log-log slope near its
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numerical resolution, while the largest scaled-discrepancy difference was
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approximately 2.22e-16. The difference did not change any recorded scientific
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disposition.
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This is a cross-hardware portability control, not an independent replication,
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a full CUDA rerun through 8,192 transitions, or a speed benchmark. The complete
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local CPU run remains the scientific authority. Executable source is stored in
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the companion GitHub repository at an immutable revision.
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evidence/horizon/zerogpu-portability/local-cpu-measurements.json
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The diff for this file is too large to render.
See raw diff
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evidence/horizon/zerogpu-portability/local-cpu-run-receipt.json
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{
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"schema": "sno.local-cpu-bounded-baseline.v1",
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"date": "2026-09-14",
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"scope": "matched-runtime local CPU execution of the frozen 32,64,128 horizon subset",
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"command": "python run_causal_horizon_breakpoint.py --horizons 32,64,128",
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"environment": {
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"python": "3.13.13",
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"platform": "macOS-27.0-arm64-arm-64bit-Mach-O",
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"numpy": "2.5.1",
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"matplotlib": "3.11.1",
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"pytorch": "2.13.0",
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"device": "host CPU",
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"dtype": "torch.float64",
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"torch_threads": 1
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},
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"checkpoint": {
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"sha256": "c57200ce04c357228a71e15478b9580322dced7b7111c7c74f05356086c71384",
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"byte_identical_to_complete_ladder_input": true
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},
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"result": {
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"measurements_sha256": "f819356aa1d25c9e306c1e91411c7c3a54377db42e516ead31aeaf786b5aece9",
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"horizons": [32, 64, 128],
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"all_statuses": ["PASS", "PASS", "PASS"],
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"all_stop_reasons_empty": true
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},
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"resources": {
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"elapsed_seconds": 151.17,
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"user_cpu_seconds": 29.75,
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"system_cpu_seconds": 24.48,
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| 30 |
+
"maximum_resident_set_bytes": 1043890176,
|
| 31 |
+
"peak_memory_footprint_bytes": 440993520,
|
| 32 |
+
"swaps": 0,
|
| 33 |
+
"measurement_tool": "/usr/bin/time -lp"
|
| 34 |
+
},
|
| 35 |
+
"claim_ceiling": "This is a matched local timing and numerical reference for the three-horizon portability subset. It is not the complete 32-through-8192 authority run."
|
| 36 |
+
}
|
evidence/horizon/zerogpu-portability/zerogpu-receipt.json
ADDED
|
@@ -0,0 +1,99 @@
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|
| 1 |
+
{
|
| 2 |
+
"checkpoint": {
|
| 3 |
+
"input_role": "byte-identical checkpoint generated by the local CPU authority path",
|
| 4 |
+
"matches_cpu_authority": true,
|
| 5 |
+
"sha256": "c57200ce04c357228a71e15478b9580322dced7b7111c7c74f05356086c71384"
|
| 6 |
+
},
|
| 7 |
+
"comparison": {
|
| 8 |
+
"all_horizon_decisions_agree": true,
|
| 9 |
+
"all_numeric_values_close_rtol_1e-9_atol_1e-12": false,
|
| 10 |
+
"cpu_reference_sha256": "b48af9b94fe9d5b0e54300d1633349c055c064e694d212ce2818bb52e2f72b7a",
|
| 11 |
+
"horizons": [
|
| 12 |
+
32,
|
| 13 |
+
64,
|
| 14 |
+
128
|
| 15 |
+
],
|
| 16 |
+
"numeric_leaf_count": 2373,
|
| 17 |
+
"per_horizon": [
|
| 18 |
+
{
|
| 19 |
+
"all_records_finite": true,
|
| 20 |
+
"decision_agreement": true,
|
| 21 |
+
"each_order_improves_alpha_one": true,
|
| 22 |
+
"event_positions_match_cpu": true,
|
| 23 |
+
"finite_baseline": true,
|
| 24 |
+
"horizon": 32,
|
| 25 |
+
"residual_order_dispositions_match_cpu": true,
|
| 26 |
+
"status": "PASS",
|
| 27 |
+
"status_matches_cpu": true,
|
| 28 |
+
"stop_reasons_match_cpu": true,
|
| 29 |
+
"third_order_material_sign_accuracy": 1.0,
|
| 30 |
+
"third_order_relative_mae": 4.270185763311071e-08
|
| 31 |
+
},
|
| 32 |
+
{
|
| 33 |
+
"all_records_finite": true,
|
| 34 |
+
"decision_agreement": true,
|
| 35 |
+
"each_order_improves_alpha_one": true,
|
| 36 |
+
"event_positions_match_cpu": true,
|
| 37 |
+
"finite_baseline": true,
|
| 38 |
+
"horizon": 64,
|
| 39 |
+
"residual_order_dispositions_match_cpu": true,
|
| 40 |
+
"status": "PASS",
|
| 41 |
+
"status_matches_cpu": true,
|
| 42 |
+
"stop_reasons_match_cpu": true,
|
| 43 |
+
"third_order_material_sign_accuracy": 1.0,
|
| 44 |
+
"third_order_relative_mae": 1.8160403187706612e-08
|
| 45 |
+
},
|
| 46 |
+
{
|
| 47 |
+
"all_records_finite": true,
|
| 48 |
+
"decision_agreement": true,
|
| 49 |
+
"each_order_improves_alpha_one": true,
|
| 50 |
+
"event_positions_match_cpu": true,
|
| 51 |
+
"finite_baseline": true,
|
| 52 |
+
"horizon": 128,
|
| 53 |
+
"residual_order_dispositions_match_cpu": true,
|
| 54 |
+
"status": "PASS",
|
| 55 |
+
"status_matches_cpu": true,
|
| 56 |
+
"stop_reasons_match_cpu": true,
|
| 57 |
+
"third_order_material_sign_accuracy": 1.0,
|
| 58 |
+
"third_order_relative_mae": 5.018142262065098e-08
|
| 59 |
+
}
|
| 60 |
+
],
|
| 61 |
+
"worst_absolute_error": {
|
| 62 |
+
"absolute_error": 0.0007027303143045671,
|
| 63 |
+
"actual": 3.997895366576603,
|
| 64 |
+
"expected": 3.9971926362622985,
|
| 65 |
+
"field_path": "/0/summaries/3/final/mae_log_log_fit/slope",
|
| 66 |
+
"scaled_error": 0.00017577506409486522
|
| 67 |
+
},
|
| 68 |
+
"worst_scaled_error": {
|
| 69 |
+
"absolute_error": 2.220477812985835e-16,
|
| 70 |
+
"actual": 1.3713029311661655e-16,
|
| 71 |
+
"expected": -8.491748818196697e-17,
|
| 72 |
+
"field_path": "/2/records/3/order_3_residual",
|
| 73 |
+
"scaled_error": 0.2220477812985835
|
| 74 |
+
}
|
| 75 |
+
},
|
| 76 |
+
"elapsed_seconds": 24.83867708593607,
|
| 77 |
+
"environment": {
|
| 78 |
+
"cuda_capability": [
|
| 79 |
+
12,
|
| 80 |
+
0
|
| 81 |
+
],
|
| 82 |
+
"cuda_device": "NVIDIA RTX PRO 6000 Blackwell Server Edition MIG 2g.48gb",
|
| 83 |
+
"cuda_runtime": "13.0",
|
| 84 |
+
"dtype": "torch.float64",
|
| 85 |
+
"observed_tensor_device": "cuda:0",
|
| 86 |
+
"platform": "Linux-6.12.94-123.192.amzn2023.x86_64-x86_64-with-glibc2.41",
|
| 87 |
+
"python": "3.12.12",
|
| 88 |
+
"pytorch": "2.13.0+cu130",
|
| 89 |
+
"torch_threads": 1
|
| 90 |
+
},
|
| 91 |
+
"interpretation": {
|
| 92 |
+
"authority": "The complete local PyTorch 2.13 float64 CPU ladder remains authoritative.",
|
| 93 |
+
"claim_ceiling": "This run does not establish bitwise cross-platform identity, full 8192-horizon CUDA reproduction, or a fair CPU-versus-GPU speed comparison.",
|
| 94 |
+
"positive_result": "A pass means the bounded CUDA run preserves the frozen checkpoint and selected scientific decisions within the declared numerical tolerance."
|
| 95 |
+
},
|
| 96 |
+
"receipt_sha256": "25fde7e9ba3d3c758a097dec359a48ad009b95d12e23b2a1cecb1bc5fc061de6",
|
| 97 |
+
"schema": "sno.zerogpu-portability-baseline.v1",
|
| 98 |
+
"scope": "bounded 32,64,128-horizon CUDA portability control; not the 8192-step authority and not a performance comparison"
|
| 99 |
+
}
|