[
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    "50.00 percentile latency (ns)": 1023738,
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    "90th percentile latency (ns)": 1046296,
    "95.00 percentile latency (ns)": 1053978,
    "97.00 percentile latency (ns)": 1060265,
    "99.00 percentile latency (ns)": 1071648,
    "99.90 percentile latency (ns)": 1122214,
    "Max latency (ns)": 2995294,
    "Mean latency (ns)": 1028177,
    "Min duration satisfied": "Yes",
    "Min latency (ns)": 991959,
    "Min queries satisfied": "Yes",
    "Mode": "Performance",
    "QPS w/ loadgen overhead": 956.73,
    "QPS w/o loadgen overhead": 972.6,
    "Result is": "VALID",
    "SUT name": "PySUT",
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    "accelerator_interconnect": "-",
    "accelerator_interconnect_topology": "-",
    "accelerator_memory_capacity": "4GB",
    "accelerator_memory_configuration": "none",
    "accelerator_model_name": "Centaur Integrated AI Coprocessor",
    "accelerator_on-chip_memories": "-",
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    "characteristics.90th_percentile_latency_us": 1046.296,
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    "ck_system": "0",
    "ck_used": true,
    "dataset": "ImageNet 2012",
    "dataset_link": "https://github.com/ctuning/ck/blob/master/docs/mlperf-automation/datasets/imagenet2012.md",
    "dim_x_default": "characteristics.90th_percentile_latency_ms",
    "dim_y_default": "characteristics.accuracy",
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    "division": "closed",
    "formal_model": "resnet50-v1.5",
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    "framework": "TensorFlow commit f5ce1c00d4397875ff3d706881bd46430f4a9667 and f6fbfe013898dc16bd35ba380387ff02d0275ac3 + custom patches",
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    "host_storage_capacity": "120GB",
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    "note_code": "https://github.com/mlcommons/inference_results_v0.5/tree/master/closed/CentaurTechnology/code",
    "note_details": "https://github.com/mlcommons/inference_results_v0.5/tree/master/closed/CentaurTechnology/results/0",
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    "operating_system": "Ubuntu 18.04.5 LTS (Linux-5.4.0-1055-azure-x86_64-with-Ubuntu-18.04-bionic)",
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    "performance_issue_unique": true,
    "performance_sample_count": 1024,
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    "retraining": "none",
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    "status": "preview",
    "submitter": "CentaurTechnology",
    "submitter_link": "https://github.com/ctuning/ck-mlperf-inference/tree/main/bench.mlperf.submitter/CentaurTechnology",
    "sw_notes": "The same hardware system is used for all mobilenet, resnet, ssd-small, and gnmt sumbissions, but the software is slightly different for gnmt. Submissions for mobilenet, resnet, and ssd-small use TF commit f5ce1c00d4397875ff3d706881bd46430f4a9667 + custom patches to TF-Lite, Centaur ML Library Build 1223, and host_processor_frequency set to 2.5GHz. Submissions for gnmt use TF commit f6fbfe013898dc16bd35ba380387ff02d0275ac3 + custom patches for compiler/graph matching, Centaur ML Library Build 1220, and host_processor_frequency set at runtime via software to 2.3GHz.Powered by CK v2.5.8 (https://github.com/ctuning/ck)",
    "system_link": "https://github.com/ctuning/ck-mlperf-inference/tree/main/bench.mlperf.system/0",
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    "weight_transformations": "TF-Lite v1.14"
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    "90th percentile latency (ns)": 328674,
    "95.00 percentile latency (ns)": 347811,
    "97.00 percentile latency (ns)": 352420,
    "99.00 percentile latency (ns)": 363107,
    "99.90 percentile latency (ns)": 383849,
    "Max latency (ns)": 1882299,
    "Mean latency (ns)": 324817,
    "Min duration satisfied": "Yes",
    "Min latency (ns)": 311493,
    "Min queries satisfied": "Yes",
    "Mode": "Performance",
    "QPS w/ loadgen overhead": 2934.63,
    "QPS w/o loadgen overhead": 3078.66,
    "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",
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    "ck_used": true,
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    "dataset_link": "https://github.com/ctuning/ck/blob/master/docs/mlperf-automation/datasets/imagenet2012.md",
    "dim_x_default": "characteristics.90th_percentile_latency_ms",
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    "host_processor_model_name": "AMD EPYC 7V13 64-Core Processor",
    "host_processors_per_node": 1,
    "host_storage_capacity": "120GB",
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    "note_code": "https://github.com/mlcommons/inference_results_v0.5/tree/master/closed/CentaurTechnology/code",
    "note_details": "https://github.com/mlcommons/inference_results_v0.5/tree/master/closed/CentaurTechnology/results/0",
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    "operating_system": "Ubuntu 18.04.5 LTS (Linux-5.4.0-1055-azure-x86_64-with-Ubuntu-18.04-bionic)",
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    "status": "preview",
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    "submitter_link": "https://github.com/ctuning/ck-mlperf-inference/tree/main/bench.mlperf.submitter/CentaurTechnology",
    "sw_notes": "The same hardware system is used for all mobilenet, resnet, ssd-small, and gnmt sumbissions, but the software is slightly different for gnmt. Submissions for mobilenet, resnet, and ssd-small use TF commit f5ce1c00d4397875ff3d706881bd46430f4a9667 + custom patches to TF-Lite, Centaur ML Library Build 1223, and host_processor_frequency set to 2.5GHz. Submissions for gnmt use TF commit f6fbfe013898dc16bd35ba380387ff02d0275ac3 + custom patches for compiler/graph matching, Centaur ML Library Build 1220, and host_processor_frequency set at runtime via software to 2.3GHz.Powered by CK v2.5.8 (https://github.com/ctuning/ck)",
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    "system_name": "Microsoft Corporation 7.0 (Virtual Machine)",
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    "weight_data_types": "uint8",
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]