[
  {
    "50.00 percentile latency (ns)": 1294722,
    "90.00 percentile latency (ns)": 1325243,
    "90th percentile latency (ns)": 1325243,
    "95.00 percentile latency (ns)": 1336068,
    "97.00 percentile latency (ns)": 1342354,
    "99.00 percentile latency (ns)": 1353528,
    "99.90 percentile latency (ns)": 1404233,
    "Max latency (ns)": 2175214,
    "Mean latency (ns)": 1298049,
    "Min duration satisfied": "Yes",
    "Min latency (ns)": 1241991,
    "Min queries satisfied": "Yes",
    "Mode": "Performance",
    "QPS w/ loadgen overhead": 760.92,
    "QPS w/o loadgen overhead": 770.39,
    "Result is": "VALID",
    "SUT name": "PySUT",
    "Scenario": "singlestream",
    "accelerator_frequency": "-",
    "accelerator_host_interconnect": "-",
    "accelerator_interconnect": "-",
    "accelerator_interconnect_topology": "-",
    "accelerator_memory_capacity": "4GB",
    "accelerator_memory_configuration": "none",
    "accelerator_model_name": "Centaur Integrated AI Coprocessor",
    "accelerator_on-chip_memories": "-",
    "accelerators_per_node": 1,
    "accuracy_log_probability": 0,
    "accuracy_log_rng_seed": 0,
    "accuracy_log_sampling_target": 0,
    "characteristics.90th_percentile_latency_ms": 1.325243,
    "characteristics.90th_percentile_latency_ns": 1325243.0,
    "characteristics.90th_percentile_latency_s": 0.001325243,
    "characteristics.90th_percentile_latency_us": 1325.243,
    "characteristics.mAP": 23.039,
    "ck_system": "0",
    "ck_used": false,
    "dataset": "COCO 2017 (300x300)",
    "dataset_link": "https://github.com/ctuning/ck/blob/master/docs/mlperf-automation/datasets/coco2017.md",
    "dim_x_default": "characteristics.90th_percentile_latency_ms",
    "dim_y_default": "characteristics.mAP",
    "dim_y_maximize": true,
    "division": "closed",
    "formal_model": "ssd-mobilenet",
    "formal_model_accuracy": 99.0,
    "formal_model_link": "https://github.com/mlcommons/ck-mlops/tree/main/package",
    "framework": "TensorFlow-Lite 2.2.0 + custom patches, PyTorch 1.6.0",
    "host_memory_capacity": "64GB",
    "host_processor_core_count": 8,
    "host_processor_frequency": "2.5GHz",
    "host_processor_model_name": "Centaur Integrated x86 CPUs",
    "host_processors_per_node": 1,
    "host_storage_capacity": "1TB",
    "host_storage_type": "SSD",
    "informal_model": "ssd-small",
    "input_data_types": "uint8",
    "key.accuracy": "characteristics.mAP",
    "max_async_queries": 1,
    "max_duration (ms)": 0,
    "max_query_count": 0,
    "min_duration (ms)": 60000,
    "min_query_count": 1024,
    "mlperf_version": 0.7,
    "normalize_cores": 1,
    "normalize_processors": 1,
    "note_code": "https://github.com/mlcommons/inference_results_v0.7/tree/master/closed/CentaurTechnology/code",
    "note_details": "https://github.com/mlcommons/inference_results_v0.7/tree/master/closed/CentaurTechnology/results/0",
    "number_of_nodes": 1,
    "operating_system": "Ubuntu 18.04",
    "other_software_stack": "Centaur ML Library v1.0.0",
    "performance_issue_same": true,
    "performance_issue_same_index": 0,
    "performance_issue_unique": true,
    "performance_sample_count": 256,
    "print_timestamps": true,
    "problem": false,
    "qsl_rng_seed": 12786827339337101903,
    "retraining": "none",
    "sample_index_rng_seed": 12640797754436136668,
    "samples_per_query": 1,
    "schedule_rng_seed": 3135815929913719677,
    "starting_weights_filename": "https://zenodo.org/record/3252084/files/mobilenet_v1_ssd_8bit_finetuned.tar.gz",
    "status": "available",
    "submitter": "CentaurTechnology",
    "submitter_link": "https://github.com/ctuning/ck-mlperf-inference/tree/main/bench.mlperf.submitter/CentaurTechnology",
    "sw_notes": "ResNet50 and SSD-MobileNetV1 use TensorFlow-Lite, while SSD-ResNet34 uses PyTorch.",
    "system_link": "https://github.com/ctuning/ck-mlperf-inference/tree/main/bench.mlperf.system/0",
    "system_name": "Centaur Technology Reference Design v1.0D",
    "system_type": "edge",
    "target_latency (ns)": 0,
    "target_qps": 1111.11,
    "task": "object detection",
    "task2": "object detection",
    "total_cores": 8,
    "uid": "2c4c3394ad603edd",
    "use_accelerator": true,
    "weight_data_types": "uint8",
    "weight_transformations": "TF-Lite v2.2.0"
  }
]