{
  "schema_version": "slac.benchmark_definition/v0.1",
  "benchmark_id": "glim-complete-continuous-time-cuda",
  "title": "Public GLIM Livox complete continuous-time refinement",
  "protocol": {
    "protocol_id": "glim-cuda-fresh-subprocess-v5",
    "dataset_id": "glim_versatile",
    "dataset_doi": "10.5281/zenodo.6864654",
    "dataset_source_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
    "data_license": "CC-BY-4.0 (AIST Zenodo record 6864654)",
    "split_policy": "Latest capture frames held out; repeats share the same accuracy fixture",
    "splits": [
      {
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        "seed": 0,
        "fit_count": 6000,
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        "fit_ids_sha256": "8396d3bb0e0ad9134aafbb7e812eadd3110dfc75a18ddd201e10e6d1a5c50386",
        "holdout_ids_sha256": "0ca2151339586575d990b37935a6b44627e981399845f0f51c4f18c08afb2af1"
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        "seed": 0,
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        "fit_ids_sha256": "8396d3bb0e0ad9134aafbb7e812eadd3110dfc75a18ddd201e10e6d1a5c50386",
        "holdout_ids_sha256": "0ca2151339586575d990b37935a6b44627e981399845f0f51c4f18c08afb2af1"
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        "split_id": "repeat-03",
        "seed": 0,
        "fit_count": 6000,
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        "fit_ids_sha256": "8396d3bb0e0ad9134aafbb7e812eadd3110dfc75a18ddd201e10e6d1a5c50386",
        "holdout_ids_sha256": "0ca2151339586575d990b37935a6b44627e981399845f0f51c4f18c08afb2af1"
      },
      {
        "split_id": "repeat-04",
        "seed": 0,
        "fit_count": 6000,
        "holdout_count": 3200,
        "fit_ids_sha256": "8396d3bb0e0ad9134aafbb7e812eadd3110dfc75a18ddd201e10e6d1a5c50386",
        "holdout_ids_sha256": "0ca2151339586575d990b37935a6b44627e981399845f0f51c4f18c08afb2af1"
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      {
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        "seed": 0,
        "fit_count": 6000,
        "holdout_count": 3200,
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        "holdout_ids_sha256": "0ca2151339586575d990b37935a6b44627e981399845f0f51c4f18c08afb2af1"
      }
    ],
    "initial_estimate_policy": "Same supplied public config, initial estimate and temporal split",
    "tuning_policy": "Reverse order every other repeat; child OMP_NUM_THREADS=1",
    "failure_policy": "Keep all timings and mismatches; no warmup or excluded outliers"
  },
  "metrics": [
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      "primary": false,
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      "interpretation": "Complete clock profile and extrinsic solver call"
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      "interpretation": "Sum of adaptive nearest-plane call durations, including wrapper overhead; durations can overlap for parallel candidates"
    },
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      "primary": false,
      "interpretation": "Actual adaptive nearest-plane calls in the complete run"
    },
    {
      "name": "worker_import_seconds",
      "label": "worker_import_seconds",
      "unit": "s",
      "display_scale": 1.0,
      "direction": "lower",
      "primary": false,
      "interpretation": "Worker entry through imports, excluding interpreter startup"
    },
    {
      "name": "uniform_normal_calculations",
      "label": "uniform_normal_calculations",
      "unit": "calls",
      "display_scale": 1.0,
      "direction": "lower",
      "primary": false,
      "interpretation": "Actual uniform geometric fallback calls"
    },
    {
      "name": "interpolated_pose_calculations",
      "label": "interpolated_pose_calculations",
      "unit": "calls",
      "display_scale": 1.0,
      "direction": "lower",
      "primary": false,
      "interpretation": "Interior odometry SE3 interpolation calls"
    },
    {
      "name": "worker_cpu_seconds",
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      "unit": "s",
      "display_scale": 1.0,
      "direction": "lower",
      "primary": false,
      "interpretation": "All-thread process CPU from worker entry through saved-result hash; excludes interpreter startup and measurement JSON serialization"
    },
    {
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      "label": "subprocess_wall_seconds",
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      "display_scale": 1.0,
      "direction": "lower",
      "primary": true,
      "interpretation": "Fresh complete process wall, including artifact saves"
    },
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      "unit": "bool",
      "display_scale": 1.0,
      "direction": "higher",
      "primary": false,
      "interpretation": "All artifact values except the exact kernel identity note"
    }
  ],
  "methods": [
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      "label": "baseline",
      "implementation": "subprocess",
      "tool_name": "Calibrex",
      "tool_version": "0.5.1",
      "source_commit": "a1ff874ab0dbc39c2dacc9607f40841c610997d7",
      "adapter_version": "continuous-time-cuda/v5"
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      "tool_name": "Calibrex",
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      "source_commit": "b9eadf0f2a14c1c8993d85bcb2da29a73878893c",
      "adapter_version": "continuous-time-cuda/v5"
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  "trials": [
    {
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      "split_id": "repeat-01",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
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        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 14.229013500036672,
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      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker baseline --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/baseline.repeat-01 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
        "execution_host": "Windows-11-10.0.26300-SP0",
        "notes": [
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profile re-solves the six-DoF extrinsic at every clock candidate\",\"target holdout is the latest capture frame group and is never used for optimization\",\"train diagnostics summarize only the selected train factor and train profile\",\"trajectory_model is piecewise SE(3) interpolation of supplied odometry; trajectory knots are fixed\",\"train_frame_count=28\",\"holdout_frame_count=8\",\"holdout_start_fraction=0.8\",\"sampling_seed=0\",\"source_record_cap=6000\",\"target_point_cap_per_split=6000\",\"outlier_policy=mad\",\"voxel_strategy=adaptive\",\"replay_source_message_count=1\",\"adaptive correspondences use a uniform voxel fallback and select the lower initial point-to-plane residual\",\"continuous_time_query_execution: 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        ]
      }
    },
    {
      "method_id": "sparse",
      "split_id": "repeat-01",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.14326060051098466,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 12.682836399995722,
        "solver_seconds": 11.772035000030883,
        "subprocess_wall_seconds": 15.580717699951492,
        "uniform_normal_calculations": 883.0,
        "worker_cpu_seconds": 16.390625,
        "worker_import_seconds": 2.1201762999407947
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      "runtime_seconds": 15.580717699951492,
      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker sparse --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/sparse.repeat-01 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
        "execution_host": "Windows-11-10.0.26300-SP0",
        "notes": [
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        ]
      }
    },
    {
      "method_id": "sparse",
      "split_id": "repeat-02",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.12490749964490533,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 3.085743199917488,
        "solver_seconds": 2.274641799973324,
        "subprocess_wall_seconds": 5.3820224000373855,
        "uniform_normal_calculations": 883.0,
        "worker_cpu_seconds": 6.46875,
        "worker_import_seconds": 1.7848706000950187
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      "runtime_seconds": 5.3820224000373855,
      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker sparse --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/sparse.repeat-02 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
        "execution_host": "Windows-11-10.0.26300-SP0",
        "notes": [
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    },
    {
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      "split_id": "repeat-02",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.12509710039012134,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 3.1720257999841124,
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      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker baseline --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/baseline.repeat-02 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
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      }
    },
    {
      "method_id": "baseline",
      "split_id": "repeat-03",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.13274399982765317,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 3.4872418999439105,
        "solver_seconds": 2.527772899949923,
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      "runtime_seconds": 5.992306599975564,
      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker baseline --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/baseline.repeat-03 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
        "execution_host": "Windows-11-10.0.26300-SP0",
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        ]
      }
    },
    {
      "method_id": "sparse",
      "split_id": "repeat-03",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.11857090017292649,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 2.9755428000353277,
        "solver_seconds": 2.1612474999856204,
        "subprocess_wall_seconds": 5.313002599985339,
        "uniform_normal_calculations": 883.0,
        "worker_cpu_seconds": 6.28125,
        "worker_import_seconds": 1.8377008000388741
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      "runtime_seconds": 5.313002599985339,
      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker sparse --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/sparse.repeat-03 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
        "execution_host": "Windows-11-10.0.26300-SP0",
        "notes": [
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      }
    },
    {
      "method_id": "sparse",
      "split_id": "repeat-04",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.12807349988725036,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 3.0499093000544235,
        "solver_seconds": 2.2545116000110283,
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      "runtime_seconds": 5.456039099954069,
      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker sparse --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/sparse.repeat-04 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
        "execution_host": "Windows-11-10.0.26300-SP0",
        "notes": [
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    },
    {
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      "split_id": "repeat-04",
      "status": "success",
      "metrics": {
        "adaptive_query_calls": 184000.0,
        "adaptive_query_seconds": 0.12865599989891052,
        "complete_result_matches": 1.0,
        "interpolated_pose_calculations": 99391.0,
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      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker baseline --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/baseline.repeat-04 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
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        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
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    },
    {
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      "status": "success",
      "metrics": {
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        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker baseline --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/baseline.repeat-05 --candidate-query-backend cuda --baseline-query-backend cuda",
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    },
    {
      "method_id": "sparse",
      "split_id": "repeat-05",
      "status": "success",
      "metrics": {
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        "adaptive_query_seconds": 0.16588180023245513,
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        "interpolated_pose_calculations": 99391.0,
        "pipeline_seconds": 3.6432064999826252,
        "solver_seconds": 2.708229499985464,
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      "provenance": {
        "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --worker sparse --baseline-scope cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --output-dir <WORKSPACE>/outputs/public-glim-cuda-associations-default-v3/sparse.repeat-05 --candidate-query-backend cuda --baseline-query-backend cuda",
        "config_sha256": "677b4b8eed3a989949e37da0bc6fc59124262805151e6ab154ee2a5576387e55",
        "input_sha256": "107e3deb3aaeab52628a93d8c6eed80aa1663c3492f6a4d2e280d553e47cd27c",
        "output_sha256": "765928040d0679b110d72a3148b7c37f6ce79dfc0ceb9c95199993f4f7255195",
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        "notes": [
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          "{\"config_path\":\"examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml\",\"dataset_path\":\"data/public/glim_versatile/livox_rosbag2_gt_restamped\",\"estimated_time_offset_sec\":-0.04,\"final_holdout_rmse_m\":0.05078387183780445,\"final_train_rmse_m\":0.030992997998017136,\"holdout_correspondence_count\":2526,\"initial_time_offset_sec\":0.0,\"initial_train_rmse_m\":0.04356229285396421,\"initial_transform\":{\"child\":\"livox_avia_copy\",\"convention\":\"T_parent_child\",\"estimate_id\":\"T_livox_avia_livox_avia_copy\",\"parent\":\"livox_avia\",\"provenance\":{\"evidence_level\":\"unknown\",\"execution_mode\":\"online_stream\",\"notes\":[\"clock offset was profiled with extrinsic re-optimization\",\"supplied piecewise odometry trajectory remained 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        ]
      }
    }
  ],
  "reference_method_id": "baseline",
  "bootstrap_samples": 1,
  "bootstrap_seed": 0,
  "limitations": [
    "Single public sensor duplicated as an identity control; no absolute two-sensor accuracy claim.",
    "Fresh interpreters; no warmup or outlier exclusion; OS caches persist.",
    "Scope cuda substitutes 12 modules. All candidates, refinements, train/holdout budgets and writers are shared. Module filenames and source/input bytes are verified.",
    "Wall includes startup, imports, replay, optimization, diagnostics, input hashes, YAML output and worker measurement save; parent audits and CLI presentation are excluded.",
    "Phase timers wrap existing calls without extra work; their wrapper cost is included.",
    "Full saved/API artifacts and git revision are retained. Comparison normalizes path separators and excludes only the exact optional kernel identity note.",
    "Numba cache policy is recorded per trial, with compiled file hashes before/after. The first candidate uses an empty cache; all import/compile/load work is inside wall.",
    "Compiled scope gives each method its own persistent cache, initially empty.",
    "Candidate execution override: cuda; baseline execution override: cuda; all physical options and splits are shared. CUDA runs also own a fresh persistent kernel cache with trial-level before/after digests; compilation stays inside wall. CUDA dispatch retains CPU execution below the 8192-row capture budget.",
    "Worker CPU sums all worker threads from entry through the saved-result hash; interpreter startup and measurement JSON serialization are outside that diagnostic.",
    "Raw checksums and conversion lineage are verified before measurement.",
    "Split IDs hash ordered sampled target indices, capture timestamps and XYZ; the distinct temporal partitions and unchanged sampling caps are verified each run.",
    "Descriptive timings are local observations, not portable confidence estimates."
  ],
  "provenance": {
    "generator": "tools.benchmark_adaptive_plane_search",
    "generator_version": "v0.5",
    "generated_at": "2026-10-13T00:07:29.601305+00:00",
    "git_commit": "b9eadf0",
    "command": "<PYTHON> <WORKSPACE>/tools/benchmark_adaptive_plane_search.py --baseline-scope cuda --baseline-commit a1ff874ab0dbc39c2dacc9607f40841c610997d7 --candidate-query-backend cuda --baseline-query-backend cuda --config examples/public_datasets/glim_versatile/online_continuous_time_compiled_queries_config.yaml --repetitions 5 --output-dir outputs/public-glim-cuda-associations-default-v3",
    "source_artifacts": {
      "baseline.adaptive_voxel.py.txt": "8092345b64133e7f80680e6283cf5da1950b098881327ce62b0dfec22e10acb1",
      "baseline.continuous_time_lidar_pair_solver.py.txt": "d93e9355299930b54e65416e0faf4411e14439c304be5567bb0e51345d876534",
      "baseline.cuda_continuous_time_adapter.py.txt": "b6b9761ec85e365e9b5f87321d36001b657e039741e31639a0b5214883d5c048",
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