{ "benchmark_id": "d2d-projection-kitti_raw_2011_09_30_drive_0018", "bootstrap_samples": 1000, "bootstrap_seed": 42, "limitations": [ "All timed projections and MI records exactly match the NumPy reference.", "Timing repetitions are not held-out calibration accuracy trials.", "Transfers and synchronization are included; compilation/preparation are separate.", "Startup times: {\"cuda\": {\"first_evaluation_seconds\": 0.1885257000103593, \"setup_seconds\": 0.8845528999809176}, \"cuda_cache_2048_mib\": {\"first_evaluation_seconds\": 0.03803569998126477, \"setup_seconds\": 0.1637885000091046}, \"numpy\": {\"first_evaluation_seconds\": 3.1187023000093177, \"setup_seconds\": 7.800001185387373e-06}}", "Environment: Python 3.12.10; NumPy 2.3.4; Windows-11-10.0.26300-SP0; CPU Intel64 Family 6 Model 158 Stepping 10, GenuineIntel", "Workload: 25 frames; 33173268 total points; camera grids: [(1226, 370, 'pinhole')]", "Digest-verified real inputs measure backend equivalence and latency; this timing experiment is not a calibration accuracy benchmark.", "CUDA allocation snapshots (bytes): {\"after_first_evaluation\": {\"cache_budget_bytes\": 268435456, \"cached_input_bytes\": 268045632, \"device_total_bytes\": 6442123264, \"device_used_bytes\": 1518010368, \"evaluation_input_upload_bytes\": 884222944, \"evaluation_input_upload_calls\": 19, \"pool_reserved_bytes\": 432396288, \"pool_used_bytes\": 268050432, \"preparation_input_upload_bytes\": 268045632, \"preparation_input_upload_calls\": 6, \"prepared_observation_count\": 6}, \"after_first_evaluation_cuda_cache_2048_mib\": {\"cache_budget_bytes\": 2147483648, \"cached_input_bytes\": 1152268576, \"device_total_bytes\": 6442123264, \"device_used_bytes\": 2637889536, \"evaluation_input_upload_bytes\": 0, \"evaluation_input_upload_calls\": 0, \"pool_reserved_bytes\": 1487757824, \"pool_used_bytes\": 1420335104, \"preparation_input_upload_bytes\": 1152268576, \"preparation_input_upload_calls\": 25, \"prepared_observation_count\": 25}, \"after_projection_timings\": {\"cache_budget_bytes\": 268435456, \"cached_input_bytes\": 268045632, \"device_total_bytes\": 6442123264, \"device_used_bytes\": 2738552832, \"evaluation_input_upload_bytes\": 6189560608, \"evaluation_input_upload_calls\": 133, \"pool_reserved_bytes\": 1587875840, \"pool_used_bytes\": 1420335104, \"preparation_input_upload_bytes\": 268045632, \"preparation_input_upload_calls\": 6, \"prepared_observation_count\": 6}, \"after_projection_timings_cuda_cache_2048_mib\": {\"cache_budget_bytes\": 2147483648, \"cached_input_bytes\": 1152268576, \"device_total_bytes\": 6442123264, \"device_used_bytes\": 2738552832, \"evaluation_input_upload_bytes\": 0, \"evaluation_input_upload_calls\": 0, \"pool_reserved_bytes\": 1587875840, \"pool_used_bytes\": 1420335104, \"preparation_input_upload_bytes\": 1152268576, \"preparation_input_upload_calls\": 25, \"prepared_observation_count\": 25}}", "CUDA pool reservation includes reusable scratch allocations; device usage includes context/other applications. Snapshots are not process peak VRAM.", "Input upload counters cover coordinates, depth maps and LiDAR ranges, excluding small pose/bin-edge uploads and returned histograms. Preparation uploads are separate from evaluation uploads.", "Cache comparison keeps CUDA projectors resident together and rotates timing order. Pool/device snapshots include all resident projectors; cached bytes and input upload counters are per projector.", "Publication metadata normalizes local interpreter/dataset paths and host names; numerical records and original input/config/code digests are unchanged. The original local report SHA-256 is recorded in source_artifacts." ], "method_summaries": { "cuda": { "failure_count": 0, "failure_rate": 0.0, "method_id": "cuda", "metrics": { "evaluation_seconds": { "distribution": { "count": 3, "maximum": 0.3069616000284441, "mean": 0.26756563334492967, "mean_ci95_high": 0.3069616000284441, "mean_ci95_low": 0.23489510000217706, "median": 0.26084020000416785, "minimum": 0.23489510000217706, "p90": 0.2977373200235888, "p95": 0.3023494600260165, "standard_deviation": 0.029802893558900832 }, "metric": "evaluation_seconds", "rank": 2 }, "projection_seconds": { "distribution": { "count": 3, "maximum": 1.2514867999707349, "mean": 0.9851578666518132, "mean_ci95_high": 1.2514867999707349, "mean_ci95_low": 0.7707901999820024, "median": 0.9331966000027023, "minimum": 0.7707901999820024, "p90": 1.1878287599771284, "p95": 1.2196577799739317, "standard_deviation": 0.19965350858260564 }, "metric": "projection_seconds", "rank": 2 } }, "peak_memory_mb": { "count": 0 }, "runtime_seconds": { "count": 3, "maximum": 0.3069616000284441, "mean": 0.26756563334492967, "mean_ci95_high": 0.3069616000284441, "mean_ci95_low": 0.23489510000217706, "median": 0.26084020000416785, "minimum": 0.23489510000217706, "p90": 0.2977373200235888, "p95": 0.3023494600260165, "standard_deviation": 0.029802893558900832 }, "success_count": 3, "trial_count": 3 }, "cuda_cache_2048_mib": { "failure_count": 0, "failure_rate": 0.0, "method_id": "cuda_cache_2048_mib", "metrics": { "evaluation_seconds": { "distribution": { "count": 3, "maximum": 0.07255530002294108, "mean": 0.056647000019438565, "mean_ci95_high": 0.07255530002294108, "mean_ci95_low": 0.042519900016486645, "median": 0.05486580001888797, "minimum": 0.042519900016486645, "p90": 0.06901740002213046, "p95": 0.07078635002253576, "standard_deviation": 0.012326416577643369 }, "metric": "evaluation_seconds", "rank": 1 }, "projection_seconds": { "distribution": { "count": 3, "maximum": 0.7452213000506163, "mean": 0.6153808666858822, "mean_ci95_high": 0.7452213000506163, "mean_ci95_low": 0.40545030002249405, "median": 0.6954709999845363, "minimum": 0.40545030002249405, "p90": 0.7352712400374002, "p95": 0.7402462700440082, "standard_deviation": 0.14982635550056983 }, "metric": "projection_seconds", "rank": 1 } }, "peak_memory_mb": { "count": 0 }, "runtime_seconds": { "count": 3, "maximum": 0.07255530002294108, "mean": 0.056647000019438565, "mean_ci95_high": 0.07255530002294108, "mean_ci95_low": 0.042519900016486645, "median": 0.05486580001888797, "minimum": 0.042519900016486645, "p90": 0.06901740002213046, "p95": 0.07078635002253576, "standard_deviation": 0.012326416577643369 }, "success_count": 3, "trial_count": 3 }, "numpy": { "failure_count": 0, "failure_rate": 0.0, "method_id": "numpy", "metrics": { "evaluation_seconds": { "distribution": { "count": 3, "maximum": 10.21563489997061, "mean": 6.7814338666309295, "mean_ci95_high": 10.21563489997061, "mean_ci95_low": 4.231549999967683, "median": 5.897116699954495, "minimum": 4.231549999967683, "p90": 9.351931259967387, "p95": 9.783783079968998, "standard_deviation": 2.5217494801651408 }, "metric": "evaluation_seconds", "rank": 3 }, "projection_seconds": { "distribution": { "count": 3, "maximum": 7.2878145999857225, "mean": 5.161484966656038, "mean_ci95_high": 7.2878145999857225, "mean_ci95_low": 3.3628880999749526, "median": 4.833752200007439, "minimum": 3.3628880999749526, "p90": 6.797002119990065, "p95": 7.042408359987894, "standard_deviation": 1.6190158702893263 }, "metric": "projection_seconds", "rank": 3 } }, "peak_memory_mb": { "count": 0 }, "runtime_seconds": { "count": 3, "maximum": 10.21563489997061, "mean": 6.7814338666309295, "mean_ci95_high": 10.21563489997061, "mean_ci95_low": 4.231549999967683, "median": 5.897116699954495, "minimum": 4.231549999967683, "p90": 9.351931259967387, "p95": 9.783783079968998, "standard_deviation": 2.5217494801651408 }, "success_count": 3, "trial_count": 3 } }, "methods": [ { "implementation": "adapter", "label": "numpy", "license_spdx": "Apache-2.0 AND MIT AND BSD-2-Clause", "method_id": "numpy", "tool_name": "numpy", "tool_version": "calibrex.numpy_depth_pair_projector/v0.2;numpy=2.3.4" }, { "implementation": "adapter", "label": "cuda", "license_spdx": "Apache-2.0 AND MIT AND BSD-2-Clause", "method_id": "cuda", "tool_name": "cuda", "tool_version": "calibrex.cuda_depth_pair_projector/v0.2;cupy=14.2.0;numpy=2.3.4;cuda_runtime=12090;cuda_driver=13020;device=NVIDIA CUDA GPU;compute=7.5;nvrtc=12.8;kernel_sha256=63e1f2eed8bceede3572e6f1d31827e1bdf4619106aac34648b0ff0af213ab79;fp64;fmad=false" }, { "implementation": "adapter", "label": "cuda_cache_2048_mib", "license_spdx": "Apache-2.0 AND MIT AND BSD-2-Clause", "method_id": "cuda_cache_2048_mib", "tool_name": "cuda_cache_2048_mib", "tool_version": "calibrex.cuda_depth_pair_projector/v0.2;cupy=14.2.0;numpy=2.3.4;cuda_runtime=12090;cuda_driver=13020;device=NVIDIA CUDA GPU;compute=7.5;nvrtc=12.8;kernel_sha256=63e1f2eed8bceede3572e6f1d31827e1bdf4619106aac34648b0ff0af213ab79;fp64;fmad=false;cache_bytes=2147483648" } ], "metrics": [ { "direction": "lower", "display_scale": 1000.0, "display_unit": "ms", "interpretation": "synchronized warm host-to-host latency", "label": "projection_seconds", "name": "projection_seconds", "primary": true, "unit": "s" }, { "direction": "lower", "display_scale": 1000.0, "display_unit": "ms", "interpretation": "synchronized warm host-to-host latency", "label": "evaluation_seconds", "name": "evaluation_seconds", "primary": true, "unit": "s" } ], "paired_comparisons": [ { "candidate_method_id": "cuda", "direction": "lower", "improvement_ci95_high": 6.35461799998302, "improvement_ci95_low": 2.5920978999929503, "improvement_mean": 4.176327100004225, "metric": "projection_seconds", "paired_count": 3, "raw_delta_mean": -4.176327100004225, "reference_method_id": "numpy" }, { "candidate_method_id": "cuda", "direction": "lower", "improvement_ci95_high": 9.908673299942166, "improvement_ci95_low": 3.9707097999635153, "improvement_mean": 6.513868233286, "metric": "evaluation_seconds", "paired_count": 3, "raw_delta_mean": -6.513868233286, "reference_method_id": "numpy" }, { "candidate_method_id": "cuda_cache_2048_mib", "direction": "lower", "improvement_ci95_high": 6.542593299935106, "improvement_ci95_low": 2.9574377999524586, "improvement_mean": 4.546104099970155, "metric": "projection_seconds", "paired_count": 3, "raw_delta_mean": -4.546104099970155, "reference_method_id": "numpy" }, { "candidate_method_id": "cuda_cache_2048_mib", "direction": "lower", "improvement_ci95_high": 10.143079599947669, "improvement_ci95_low": 4.176684199948795, "improvement_mean": 6.724786866611491, "metric": "evaluation_seconds", "paired_count": 3, "raw_delta_mean": -6.724786866611491, "reference_method_id": "numpy" } ], "protocol": { "data_license": "synthetic Apache-2.0 or input dataset-specific", "dataset_id": "kitti_raw_2011_09_30_drive_0018", "dataset_source_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "failure_policy": "abort and report any projection, MI or solver-trace mismatch", "initial_estimate_policy": "prespecified pose perturbations shared across backends", "protocol_id": "d2d-backend-latency/v0.1", "split_policy": "paired timing repetitions; reference projection is the equivalence anchor, not accuracy holdout", "splits": [ { "fit_count": 25, "fit_ids_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "holdout_count": 1, "holdout_ids_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "seed": 0, "split_id": "0" }, { "fit_count": 25, "fit_ids_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "holdout_count": 1, "holdout_ids_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "seed": 1, "split_id": "1" }, { "fit_count": 25, "fit_ids_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "holdout_count": 1, "holdout_ids_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "seed": 2, "split_id": "2" } ], "tuning_policy": "FP64 and original histogram settings; no solver or metric retuning" }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "data_verified": true, "generated_at": "2026-10-10T20:22:31.533180+00:00", "generator": "tools.benchmark_d2d_projection", "generator_version": "v0.3", "git_commit": "fe0c7d6", "source_artifacts": { "config": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "input": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "local_report_before_publication": "d6f1db3fd66a344b717a5041031784643e59ce260a0c5fff3a7d08c88588cd92", "src\\calibrex\\solvers\\borer_depth_to_depth_solver.py": "ef1ea2fe9e03d6e9d67855a58bde705355ef1332e5b10f5806c8c86e6fb5b70f", "src\\calibrex\\solvers\\borer_six_dof_solver.py": "94ffd07c6977a83bf2e7ac5d5c19e0a3e2725ef7510dfa1e7d3c82ba08a89baa", "src\\calibrex\\solvers\\cuda_depth_to_depth_adapter.py": "b04102f28c1d52d1654013291425f9ba4ccdb31f0cf66b22776f161b27d5e93d", "src\\calibrex\\solvers\\depth_to_depth_runtime.py": "1fe1da440a4bae96d836e874869170717ff1dba818767531360ff0bae031c45c", "tools\\benchmark_d2d_projection.py": "734d86dce9d722711efca10088148787bcbabe17f5d5ccee646e331ff0a5d36e" } }, "reference_method_id": "numpy", "schema_version": "slac.benchmark/v0.1", "title": "D2D projection backend latency: kitti_raw_2011_09_30_drive_0018", "trials": [ { "method_id": "numpy", "metrics": { "evaluation_seconds": 5.897116699954495, "projection_seconds": 3.3628880999749526 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 5.897116699954495, "split_id": "0", "status": "success" }, { "method_id": "numpy", "metrics": { "evaluation_seconds": 10.21563489997061, "projection_seconds": 7.2878145999857225 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 10.21563489997061, "split_id": "1", "status": "success" }, { "method_id": "numpy", "metrics": { "evaluation_seconds": 4.231549999967683, "projection_seconds": 4.833752200007439 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 4.231549999967683, "split_id": "2", "status": "success" }, { "method_id": "cuda", "metrics": { "evaluation_seconds": 0.23489510000217706, "projection_seconds": 0.7707901999820024 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 0.23489510000217706, "split_id": "0", "status": "success" }, { "method_id": "cuda", "metrics": { "evaluation_seconds": 0.3069616000284441, "projection_seconds": 0.9331966000027023 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 0.3069616000284441, "split_id": "1", "status": "success" }, { "method_id": "cuda", "metrics": { "evaluation_seconds": 0.26084020000416785, "projection_seconds": 1.2514867999707349 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 0.26084020000416785, "split_id": "2", "status": "success" }, { "method_id": "cuda_cache_2048_mib", "metrics": { "evaluation_seconds": 0.042519900016486645, "projection_seconds": 0.40545030002249405 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 0.042519900016486645, "split_id": "0", "status": "success" }, { "method_id": "cuda_cache_2048_mib", "metrics": { "evaluation_seconds": 0.07255530002294108, "projection_seconds": 0.7452213000506163 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 0.07255530002294108, "split_id": "1", "status": "success" }, { "method_id": "cuda_cache_2048_mib", "metrics": { "evaluation_seconds": 0.05486580001888797, "projection_seconds": 0.6954709999845363 }, "provenance": { "command": "python tools/benchmark_d2d_projection.py --problem ${DATASET_ROOT}/calibrex_camera_lidar_v07_eval/runs/kitti_raw_0018/problem-integrated-r5.yaml --backends numpy cuda --cuda-cache-mib 256 --compare-cuda-cache-mib 2048 --repeats 3 --solve-evaluations 13 --solver-repeats 3 --output-dir outputs/d2d-cache-profile/kitti-raw-paired", "config_sha256": "a98a5999e55560e08357d6b9c6aef27b3cb8afc3aa3f333eaa396f9ff2530378", "execution_host": "${HOST}", "input_sha256": "869e64208ef5f6b6387f3f052ded88a9d80ef27995bcadd534bf259063fca5c0", "notes": [ "All timed projections and MI records exactly match the NumPy reference." ] }, "runtime_seconds": 0.05486580001888797, "split_id": "2", "status": "success" } ] }