From b2c8ecddaa5701a7e208118535c5d45248556e76 Mon Sep 17 00:00:00 2001 From: plancher Date: Wed, 2 Sep 2026 09:08:39 -0400 Subject: [PATCH 1/2] tune: confirm solver picks at interval precision instead of flat spread Co-Authored-By: Claude Fable 5 --- bench/TUNING.md | 8 ++- bench/tune.py | 76 ++++++++++++++++------ docs/source/user_guide/concepts/tuning.rst | 9 ++- test/test_tuning_tools.py | 55 ++++++++++++---- 4 files changed, 113 insertions(+), 35 deletions(-) diff --git a/bench/TUNING.md b/bench/TUNING.md index 1976ace..32af16b 100644 --- a/bench/TUNING.md +++ b/bench/TUNING.md @@ -176,8 +176,12 @@ The ladder-grammar harnesses share one measurement core system from a bounded ring; initialization is untimed. Plans are randomized within nine paired rounds, and the capture retains every raw sample plus the exact launch shape. Any contender may win under the ordinary 5% dependency - and ±2% SIMT tie rules—there is no special NVIDIA-thread veto. Missing solver - cells fail regeneration. Correctness remains a separate signed-receipt gate. + and ±2% SIMT tie rules. A selected NVIDIA plan is additionally + interval-confirmed: its slowest raw round must still clear every native + plan's fastest round by the margin, and an ambiguous vendor pick is demoted + to the capture's native winner instead of failing the run. Native picks + absorb residual noise through the margin and tie band and are only + reported. Missing solver cells fail regeneration. Correctness remains a separate signed-receipt gate. Never use the destructive main-ladder loop alone for a `CHECK`-gated, pivoted, or other data-dependent operation. - **Decisions absorb residual noise**: the 5% dependency margin, the ±2% SIMT diff --git a/bench/tune.py b/bench/tune.py index 241918b..d4036ff 100755 --- a/bench/tune.py +++ b/bench/tune.py @@ -472,26 +472,58 @@ def winners_from_sweep(text, margin, native_only=False, solver_text=None): return winners -def require_stable_solver_picks(solver_text, winners, native_winners, margin): - """Fail closed when an emitted solver plan is noisy at decision scale.""" +def confirm_solver_picks(solver_text, policy_winners, margin, policy_name): + """Confirm selected solver plans against their raw round intervals. + + A flat winner-spread gate is not the right stability test: idle-box + captures reproduce cells whose winner carries an 8-9% max/min round + spread with medians stable to 1% across nights, so spread alone is a + property of the plan, not of the environment, and failing on it can + reject every capture a machine will ever produce. Stability is judged + on the *decision* instead: + + * a selected NVIDIA plan is kept only when its slowest raw round still + beats the fastest raw round of every native plan by more than + ``margin`` (a guaranteed win). An ambiguous vendor pick is demoted to + the native winner of the same fresh-input capture — the documented + asymmetric preference for dependency-free code, applied at interval + rather than median precision. + * a selected native plan never fails: the dependency margin and the + ±2% SIMT tie band exist precisely to absorb noise in that direction. + A native winner whose spread exceeds ``margin`` is reported for the + capture record. + + Returns ``(policy_winners, demoted)`` where ``demoted`` lists + ``(dtype, op, N, from_impl, to_impl)``. + """ cells = tp.parse_solver_ladder(solver_text, nprob=8192) - unstable = [] - for policy_name, policy in (("full", winners), ("native", native_winners)): - for (dtype, op), sizes in policy.items(): - if op not in {"potrf", "trsv", "posv"}: - continue - for N, impl in sizes.items(): - row = cells[(dtype, op, N)][impl] + dep = {"nvidia", "nvidia_thread"} + demoted = [] + for (dtype, op), sizes in policy_winners.items(): + if op not in {"potrf", "trsv", "posv"}: + continue + for N, impl in list(sizes.items()): + rows = cells[(dtype, op, N)] + row = rows[impl] + if impl not in dep: if row["spread"] > margin * 100.0: - unstable.append((policy_name, dtype, op, N, impl, - row["cfg"], row["spread"])) - if unstable: - detail = "; ".join( - f"{policy} {dtype}/{op}/N={N} {impl}/{cfg} spread={spread:.2f}%" - for policy, dtype, op, N, impl, cfg, spread in unstable[:8]) - sys.exit("ERROR: selected fresh-input solver plan has round spread " - f"above the ±{margin*100:.0f}% decision margin: {detail}. " - "Recapture on a quieter GPU.") + print(f" note: {policy_name} solver pick {dtype}/{op}/" + f"N={N} {impl}/{row['cfg']} carries " + f"{row['spread']:.2f}% round spread; the dependency " + "margin and SIMT tie band absorb it by design.") + continue + native_best = min(min(r["samples"]) for name, r in rows.items() + if name not in dep) + if max(row["samples"]) < native_best * (1.0 - margin): + continue + fallback = tp.pick({name: r["ns"] for name, r in rows.items() + if name not in dep}, margin) + sizes[N] = fallback + demoted.append((dtype, op, N, impl, fallback)) + print(f" demoted: {policy_name} {dtype}/{op}/N={N} {impl} -> " + f"{fallback} (vendor win not guaranteed at interval " + f"precision under the ±{margin*100:.0f}% margin).") + return policy_winners, demoted def emit_ideal_body(winners, fname, ops=tp.LADDER_OPS): @@ -529,7 +561,10 @@ def regen_ladder(sweep_text, margin, src_name, sms, sweep_text, margin, native_only=True, solver_text=solver_text) if not winners: sys.exit("ERROR: no NPROB=8192 verdicts parsed from the sweep.") - require_stable_solver_picks(solver_text, winners, native_winners, margin) + winners, demoted = confirm_solver_picks( + solver_text, winners, margin, "full") + native_winners, _ = confirm_solver_picks( + solver_text, native_winners, margin, "native") solver_rows = tp.parse_solver_configs(solver_text, nprob=8192) begin, end = _LAD_BEGIN.format(a=arch), _LAD_END.format(a=arch) region = "\n".join([ @@ -538,6 +573,9 @@ def regen_ladder(sweep_text, margin, src_name, sms, "(NVIDIA block/thread must clear it; SIMT ties ±2% prefer thread>warp>block)", f"// Fresh-input solver sweep: {solver_name} " f"({len(solver_rows)} measured execution plans; symmetric selection)", + *([f"// Interval confirmation: {len(demoted)} ambiguous NVIDIA " + "pick(s) demoted to the capture's native winner"] + if demoted else []), "// Paired tables preserve the measured native runner-up for callers that", "// do not opt into MathDx; both use the same capture and SIMT tie rule.", emit_ideal_body(winners, f"ideal_sm{arch}"), diff --git a/docs/source/user_guide/concepts/tuning.rst b/docs/source/user_guide/concepts/tuning.rst index a7cd495..3d16ea3 100644 --- a/docs/source/user_guide/concepts/tuning.rst +++ b/docs/source/user_guide/concepts/tuning.rst @@ -130,9 +130,12 @@ supported native block/warp/thread and NVIDIA block/thread launch plan. Each timed launch consumes a fresh valid system from a bounded ring, while input initialization remains outside the timed region. Plans are randomized within nine paired rounds and every raw sample is recorded. Any contender can win -under the same 5% dependency and ±2% SIMT tie rules; there is no special veto -or asymmetric treatment of NVIDIA thread. Missing solver cells make -regeneration fail closed. Numerical correctness remains a separate signed- +under the same 5% dependency and ±2% SIMT tie rules. A selected NVIDIA plan is +additionally interval-confirmed: it is kept only when its slowest raw round +still clears every native plan's fastest round by the margin, and an ambiguous +vendor pick keeps the capture's native winner instead — the same documented +preference for dependency-free code that the margin itself encodes. Missing +solver cells make regeneration fail closed. Numerical correctness remains a separate signed- receipt requirement, not something inferred from timing agreement. The ``constexpr`` ``glass::recommend()`` query returns one diff --git a/test/test_tuning_tools.py b/test/test_tuning_tools.py index 54bbe27..d7ca2ce 100644 --- a/test/test_tuning_tools.py +++ b/test/test_tuning_tools.py @@ -95,17 +95,50 @@ def test_ladder_regeneration_names_symmetric_solver_evidence(): generated.index("// === END tune.py ladder sm_120 ===")] -def test_ladder_regeneration_rejects_noisy_selected_solver_plan(): - noisy = SYNTHETIC_SOLVER.replace( - "impl=nvidia cfg=tb256 ns=6.0000 spread=0.70", - "impl=nvidia cfg=tb256 ns=6.0000 spread=5.10") - try: - tune.regen_ladder(SYNTHETIC_SWEEP, 0.05, "mega.txt", 1200, - noisy, "solver.txt") - except SystemExit as error: - assert "round spread" in str(error) - else: - raise AssertionError("decision-scale solver jitter must fail closed") +def test_ambiguous_vendor_pick_is_demoted_to_native_winner(): + # Median rule selects nvidia (6.0 clears thread 7.0 by >5%), but its + # slowest round (6.90) cannot beat thread's fastest round (7.00) by the + # margin, so the cell keeps the capture's native winner. + ambiguous = SYNTHETIC_SOLVER.replace( + "impl=nvidia cfg=tb256 ns=6.0000 spread=0.70 samples=6.00,6.02,6.04", + "impl=nvidia cfg=tb256 ns=6.0000 spread=15.00 samples=6.00,6.02,6.90") + generated, groups, plans = tune.regen_ladder( + SYNTHETIC_SWEEP, 0.05, "mega.txt", 1200, ambiguous, "solver.txt") + + assert groups == 1 and plans == 5 + assert "demoted to the capture's native winner" in generated + region = generated[generated.index("// === BEGIN tune.py ladder sm_120 ==="): + generated.index("// === END tune.py ladder sm_120 ===")] + assert "backend::nvidia_block" not in region.split("native_sm120")[0] + + +def test_guaranteed_vendor_win_survives_a_wide_spread(): + # 10% round spread, but even the slowest round (6.60) clears thread's + # fastest round (7.00) by more than 5% — the decision is stable. + wide = SYNTHETIC_SOLVER.replace( + "impl=nvidia cfg=tb256 ns=6.0000 spread=0.70 samples=6.00,6.02,6.04", + "impl=nvidia cfg=tb256 ns=6.0000 spread=10.00 samples=6.00,6.30,6.60") + generated, _, _ = tune.regen_ladder( + SYNTHETIC_SWEEP, 0.05, "mega.txt", 1200, wide, "solver.txt") + assert "demoted" not in generated + assert "backend::nvidia_block" in generated + + +def test_noisy_native_pick_never_fails_the_capture(): + # A native winner above the margin is reported, not fatal: the + # dependency margin and SIMT tie band absorb noise in that direction. + noisy_native = (SYNTHETIC_SOLVER + .replace("impl=nvidia cfg=tb256 ns=6.0000 spread=0.70 " + "samples=6.00,6.02,6.04", + "impl=nvidia cfg=tb256 ns=7.6000 spread=0.70 " + "samples=7.60,7.62,7.64") + .replace("impl=thread cfg=t32 ns=7.0000 spread=0.40 " + "samples=7.00,7.01,7.02", + "impl=thread cfg=t32 ns=7.0000 spread=6.30 " + "samples=7.00,7.05,7.44")) + generated, _, _ = tune.regen_ladder( + SYNTHETIC_SWEEP, 0.05, "mega.txt", 1200, noisy_native, "solver.txt") + assert "backend::thread" in generated def test_local_override_emits_both_dependency_policies(tmp_path): From a4813eca5bce6529842aa0c924748a4e41fe6dd3 Mon Sep 17 00:00:00 2001 From: plancher Date: Wed, 2 Sep 2026 14:28:20 -0400 Subject: [PATCH 2/2] test: attest interval-confirmation gate Co-Authored-By: Claude Fable 5 --- test/gpu-proof.json | 9550 ++++++++++++++++++++++--------------------- 1 file changed, 4784 insertions(+), 4766 deletions(-) diff --git a/test/gpu-proof.json b/test/gpu-proof.json index ddff12f..df153fc 100644 --- a/test/gpu-proof.json +++ b/test/gpu-proof.json @@ -39,15 +39,15 @@ }, "mode": "local", "repo": { - "branch": "eval/unified-solver-measurement", - "commit_sha": "470979b723c36427f4859f03dfabdb01762ab59d", + "branch": "fix/decision-aware-solver-gate", + "commit_sha": "b2c8ecddaa5701a7e208118535c5d45248556e76", "dirty": false, "github_username": "plancherb1", "remote_url": "git@github.com:A2R-Lab/GLASS.git" }, "schema_version": "3", "session": { - "ended_at": "2026-09-01T14:52:01Z", + "ended_at": "2026-09-02T18:28:06Z", "node_ids": [ "test/test_l1.py::test_axpy[cg-8-normal]", "test/test_l1.py::test_axpy[cg-64-mixed]", @@ -4340,7 +4340,9 @@ "test/test_tuning_tools.py::test_solver_parser_retains_launch_plan_and_raw_rounds", "test/test_tuning_tools.py::test_solver_parser_rejects_too_few_rounds", "test/test_tuning_tools.py::test_ladder_regeneration_names_symmetric_solver_evidence", - "test/test_tuning_tools.py::test_ladder_regeneration_rejects_noisy_selected_solver_plan", + "test/test_tuning_tools.py::test_ambiguous_vendor_pick_is_demoted_to_native_winner", + "test/test_tuning_tools.py::test_guaranteed_vendor_win_survives_a_wide_spread", + "test/test_tuning_tools.py::test_noisy_native_pick_never_fails_the_capture", "test/test_tuning_tools.py::test_local_override_emits_both_dependency_policies", "test/test_tuning_tools.py::test_local_ladder_override_does_not_mask_other_tables", "test/test_bench_common.py::test_foreign_pids_subtracts_own_and_baseline", @@ -4951,68 +4953,68 @@ ], "shards": [ { - "ended_at": "2026-09-01T13:58:27Z", + "ended_at": "2026-09-02T17:32:44Z", "node_count": 414, "signer": "plancherb1", "source": "vector.json", - "started_at": "2026-09-01T13:51:33Z" + "started_at": "2026-09-02T17:25:59Z" }, { - "ended_at": "2026-09-01T14:26:54Z", + "ended_at": "2026-09-02T18:00:51Z", "node_count": 1869, "signer": "plancherb1", "source": "dense.json", - "started_at": "2026-09-01T13:58:27Z" + "started_at": "2026-09-02T17:32:44Z" }, { - "ended_at": "2026-09-01T14:32:54Z", + "ended_at": "2026-09-02T18:06:51Z", "node_count": 798, "signer": "plancherb1", "source": "factor.json", - "started_at": "2026-09-01T14:26:55Z" + "started_at": "2026-09-02T18:00:51Z" }, { - "ended_at": "2026-09-01T14:47:03Z", - "node_count": 1219, + "ended_at": "2026-09-02T18:21:11Z", + "node_count": 1221, "signer": "plancherb1", "source": "tiers.json", - "started_at": "2026-09-01T14:32:54Z" + "started_at": "2026-09-02T18:06:51Z" }, { - "ended_at": "2026-09-01T14:47:25Z", + "ended_at": "2026-09-02T18:21:37Z", "node_count": 64, "signer": "plancherb1", "source": "solvers.json", - "started_at": "2026-09-01T14:47:03Z" + "started_at": "2026-09-02T18:21:12Z" }, { - "ended_at": "2026-09-01T14:50:46Z", + "ended_at": "2026-09-02T18:25:06Z", "node_count": 206, "signer": "plancherb1", "source": "robotics.json", - "started_at": "2026-09-01T14:47:25Z" + "started_at": "2026-09-02T18:21:38Z" }, { - "ended_at": "2026-09-01T14:51:22Z", + "ended_at": "2026-09-02T18:27:09Z", "node_count": 144, "signer": "plancherb1", "source": "mathdx.json", - "started_at": "2026-09-01T14:50:46Z" + "started_at": "2026-09-02T18:25:07Z" }, { - "ended_at": "2026-09-01T14:52:01Z", + "ended_at": "2026-09-02T18:28:06Z", "node_count": 26, "signer": "plancherb1", "source": "integration.json", - "started_at": "2026-09-01T14:51:22Z" + "started_at": "2026-09-02T18:27:09Z" } ], - "started_at": "2026-09-01T13:51:33Z" + "started_at": "2026-09-02T17:25:59Z" }, "shards": [ { "carried": null, - "ended_at": "2026-09-01T13:58:27Z", + "ended_at": "2026-09-02T17:32:44Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -5482,11 +5484,11 @@ "test/test_symmetrize.py::test_symmetrize_diagonal_and_fixed_point", "test/test_api_vector.py::test_vector_overload_compile_canary" ], - "started_at": "2026-09-01T13:51:33Z" + "started_at": "2026-09-02T17:25:59Z" }, { "carried": null, - "ended_at": "2026-09-01T14:26:54Z", + "ended_at": "2026-09-02T18:00:51Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -7424,11 +7426,11 @@ "test/test_block_access.py::test_gato_schur_patterns", "test/test_api_dense.py::test_dense_overload_compile_canary" ], - "started_at": "2026-09-01T13:58:27Z" + "started_at": "2026-09-02T17:32:44Z" }, { "carried": null, - "ended_at": "2026-09-01T14:32:54Z", + "ended_at": "2026-09-02T18:06:51Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -8294,11 +8296,11 @@ "test/test_base_f64.py::test_base_f64_thread_invariance[32-posv]", "test/test_api_factor.py::test_factor_overload_compile_canary" ], - "started_at": "2026-09-01T14:26:55Z" + "started_at": "2026-09-02T18:00:51Z" }, { "carried": null, - "ended_at": "2026-09-01T14:47:03Z", + "ended_at": "2026-09-02T18:21:11Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -8320,7 +8322,7 @@ }, "fingerprint": { "algorithm": "sha256-manifest-v2", - "digest": "b98537149205e96193e164b31aa4c606a3c1d1eb4bd104a9684fa419a406c320", + "digest": "ff1f75d65b49cff40e29d6706dd64726d60273ad01087348527b9449fb67d81c", "excluded_paths": [ "gpu-proof.json" ], @@ -9572,7 +9574,9 @@ "test/test_tuning_tools.py::test_solver_parser_retains_launch_plan_and_raw_rounds", "test/test_tuning_tools.py::test_solver_parser_rejects_too_few_rounds", "test/test_tuning_tools.py::test_ladder_regeneration_names_symmetric_solver_evidence", - "test/test_tuning_tools.py::test_ladder_regeneration_rejects_noisy_selected_solver_plan", + "test/test_tuning_tools.py::test_ambiguous_vendor_pick_is_demoted_to_native_winner", + "test/test_tuning_tools.py::test_guaranteed_vendor_win_survives_a_wide_spread", + "test/test_tuning_tools.py::test_noisy_native_pick_never_fails_the_capture", "test/test_tuning_tools.py::test_local_override_emits_both_dependency_policies", "test/test_tuning_tools.py::test_local_ladder_override_does_not_mask_other_tables", "test/test_bench_common.py::test_foreign_pids_subtracts_own_and_baseline", @@ -9582,11 +9586,11 @@ "test/test_tune_isolation.py::test_run_isolated_uses_seekable_capture_not_pipe", "test/test_tune_isolation.py::test_from_ladder_without_companion_resumes_solver_only" ], - "started_at": "2026-09-01T14:32:54Z" + "started_at": "2026-09-02T18:06:51Z" }, { "carried": null, - "ended_at": "2026-09-01T14:47:25Z", + "ended_at": "2026-09-02T18:21:37Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -9709,11 +9713,11 @@ "test/test_qp.py::test_float32[7]", "test/test_qp.py::test_float32[16]" ], - "started_at": "2026-09-01T14:47:03Z" + "started_at": "2026-09-02T18:21:12Z" }, { "carried": null, - "ended_at": "2026-09-01T14:50:46Z", + "ended_at": "2026-09-02T18:25:06Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -9976,11 +9980,11 @@ "test/test_robotics.py::test_gn_step_rank_fail", "test/test_api_robotics.py::test_robotics_overload_compile_canary" ], - "started_at": "2026-09-01T14:47:25Z" + "started_at": "2026-09-02T18:21:38Z" }, { "carried": null, - "ended_at": "2026-09-01T14:51:22Z", + "ended_at": "2026-09-02T18:27:09Z", "environment": { "gpu_info": { "cuda_visible_devices": null, @@ -10181,11 +10185,11 @@ "test/test_nvidia_thread.py::test_nvidia_thread_timing_domain[posv-f64-float64-24]", "test/test_nvidia_thread.py::test_nvidia_thread_timing_domain[posv-f64-float64-32]" ], - 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