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INTEL XEON PLATINUM 8592+ testing with a Quanta Cloud S6Q-MB-MPS (3B05.TEL4P1 BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2312187-NE-NET50813920
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CPU Massive 2 Tests
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a
December 18 2023
  3 Hours, 20 Minutes
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December 18 2023
  3 Hours, 20 Minutes
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December 18 2023
  3 Hours, 16 Minutes
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net, "LeelaChessZero 0.30 - Backend: BLAS", Higher Results Are Better "a",66,68,68 "b",68,66,68 "c",69,68,67 "LeelaChessZero 0.30 - Backend: Eigen", Higher Results Are Better "a",816,714,797,863,833,791,890,768,688 "b",810,803,747,846,764,839,796,834,806 "c",757,845,854,871,683,894 "Xmrig 6.21 - Variant: KawPow - Hash Count: 1M", Higher Results Are Better "a",39577.3,40199.4,40032 "b",40464.5,40418.7,40151 "c",40147.7,40131.6,40448.2 "Xmrig 6.21 - Variant: Monero - Hash Count: 1M", Higher Results Are Better "a",40162.3,40526.8,40299.8 "b",39684.1,40412.2,40363.3 "c",40340.5,40270.6,39605.5 "Xmrig 6.21 - Variant: Wownero - Hash Count: 1M", Higher Results Are Better "a",42944.3,43205.9,43114.6 "b",42835.7,43066.3,43094.2 "c",43250.7,43101.6,42889 "Xmrig 6.21 - Variant: GhostRider - Hash Count: 1M", Higher Results Are Better "a",6852.3,6869.5,6867 "b",6914.6,6844.8,6813.9 "c",6783.2,6842.4,6836.7 "Xmrig 6.21 - Variant: CryptoNight-Heavy - Hash Count: 1M", Higher Results Are Better "a",40387.7,40325.8,40471.1 "b",40377.9,40309.6,40159 "c",40594.3,40257.6,40008 "Xmrig 6.21 - Variant: CryptoNight-Femto UPX2 - Hash Count: 1M", Higher Results Are Better "a",40533.4,40394.2,40350.2 "b",39966.4,40213.9,40060.9 "c",40508.8,40247.9,40236.6 "SVT-AV1 1.8 - Encoder Mode: Preset 4 - Input: Bosphorus 4K", Higher Results Are Better "a",7.117,7.192,7.159 "b",7.211,7.123,7.171 "c",7.018,7.173,7.262 "SVT-AV1 1.8 - Encoder Mode: Preset 8 - Input: Bosphorus 4K", Higher Results Are Better "a",75.375,74.399,75.643 "b",75.4,75.532,76.279 "c",74.634,75.04,75.104 "SVT-AV1 1.8 - Encoder Mode: Preset 12 - Input: Bosphorus 4K", Higher Results Are Better "a",229.705,228.563,228.353 "b",230.045,227.456,231.041 "c",225.786,230.779,228.99 "SVT-AV1 1.8 - Encoder Mode: Preset 13 - Input: Bosphorus 4K", Higher Results Are Better "a",225.069,231.741,225.046 "b",230.987,228.43,229.25 "c",229.076,228.739,229.409 "SVT-AV1 1.8 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p", Higher Results Are Better "a",20.813,20.62,20.876 "b",20.578,20.576,20.608 "c",20.027,20.862,20.588 "SVT-AV1 1.8 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p", Higher Results Are Better "a",139.667,139.642,140.125 "b",140.559,148.845,139.718,138.222,143.265,141.462,141.77 "c",143.505,138.168,143.946 "SVT-AV1 1.8 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p", Higher Results Are Better "a",545.771,554.547,537.412 "b",550.655,539.2,541.32 "c",554.637,537.961,548.032 "SVT-AV1 1.8 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p", Higher Results Are Better "a",638.922,627.094,631.36 "b",628.71,636.599,645.417 "c",646.254,632.805,632.951 "Neural Magic DeepSparse 1.6 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",71.6875,72.2104,72.0614 "b",71.366,71.9442,71.7174 "c",71.571,72.0936,72.2408 "Neural Magic DeepSparse 1.6 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",443.3832,441.4215,442.1309 "b",443.7809,443.2799,443.1305 "c",444.2538,442.3295,441.6741 "Neural Magic DeepSparse 1.6 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",34.4673,34.5156,34.4418 "b",34.5181,34.3774,34.5523 "c",34.3131,34.3041,34.0958 "Neural Magic DeepSparse 1.6 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",29.0079,28.9675,29.0295 "b",28.9653,29.0838,28.9368 "c",29.1385,29.1463,29.3241 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",2319.1618,2325.9258,2326.8521 "b",2321.9087,2330.5664,2321.7335 "c",2321.5141,2323.2871,2322.9396 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",13.7784,13.7395,13.7333 "b",13.7634,13.7111,13.7642 "c",13.766,13.7557,13.7574 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",213.1705,212.1902,207.5306 "b",211.7295,209.1484,211.552 "c",208.69,210.3457,209.7928 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",4.6855,4.7077,4.8131 "b",4.7179,4.7761,4.7218 "c",4.7859,4.7485,4.7618 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",928.2292,940.6891,935.039 "b",942.3545,931.1204,911.8637 "c",941.0583,938.1917,939.359 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",34.4508,33.9904,34.1966 "b",33.9366,34.3293,35.0731 "c",33.9834,34.0839,34.0467 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",285.1478,288.5328,286.984 "b",289.2549,290.1109,291.482 "c",287.0076,289.6269,285.4062 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",3.5037,3.4625,3.4813 "b",3.4539,3.4436,3.4275 "c",3.4805,3.4496,3.5 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",5696.48,5737.3027,5686.3066 "b",5734.5879,5698.3361,5719.6315 "c",5713.3148,5729.1242,5672.4199 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",5.6057,5.5652,5.6151 "b",5.5681,5.6031,5.5819 "c",5.5894,5.5731,5.627 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",699.5649,699.8742,705.9353 "b",711.6183,704.0124,701.8498 "c",702.1384,701.7243,701.2555 "Neural Magic DeepSparse 1.6 - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",1.4227,1.4248,1.4126 "b",1.4013,1.415,1.4206 "c",1.4208,1.4192,1.4215 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",437.1842,436.1557,436.2279 "b",435.7267,436.3614,436.8977 "c",435.1291,435.5699,435.7805 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",73.1657,73.3104,73.322 "b",73.3789,73.2917,73.21 "c",73.4867,73.4131,73.3802 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",165.4393,165.7656,163.6129 "b",165.0768,164.6764,164.9373 "c",164.2188,163.5074,164.1893 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",6.0391,6.0274,6.1066 "b",6.0523,6.0671,6.0574 "c",6.0835,6.1085,6.0847 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",86.5247,86.3303,86.0521 "b",86.4579,86.2395,86.1768 "c",86.2651,86.1514,86.0961 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",369.7799,370.5988,371.8075 "b",370.0657,370.993,371.2695 "c",370.8847,371.3863,371.6161 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",31.1945,31.2515,31.2277 "b",31.1548,31.1959,31.0889 "c",31.0375,31.2454,31.2795 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",32.0505,31.9921,32.0164 "b",32.0916,32.0488,32.1593 "c",32.2131,31.999,31.9635 "Neural Magic DeepSparse 1.6 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",925.6922,938.7342,934.5958 "b",928.5565,931.3125,943.6983 "c",939.837,940.4242,940.3983 "Neural Magic DeepSparse 1.6 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",34.5478,34.0679,34.2093 "b",34.4255,34.3396,33.8869 "c",34.0252,34.0022,33.9965 "Neural Magic DeepSparse 1.6 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",287.7512,293.169,289.1197 "b",286.7036,289.6861,289.665 "c",289.1323,291.748,288.5439 "Neural Magic DeepSparse 1.6 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",3.4721,3.4077,3.4558 "b",3.4846,3.4489,3.4492 "c",3.4554,3.4242,3.4622 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",452.3843,451.6108,452.5902 "b",452.1342,452.1923,452.1658 "c",449.4278,451.157,450.8907 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",70.7082,70.8267,70.6769 "b",70.7433,70.7378,70.7426 "c",71.1744,70.8965,70.943 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",166.0641,167.2108,166.6952 "b",166.6663,166.0255,166.845 "c",165.9453,166.3637,166.6059 "Neural Magic DeepSparse 1.6 - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",6.0186,5.9776,5.9949 "b",5.997,6.0193,5.9906 "c",6.0224,6.0076,5.9989 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",640.2001,641.598,641.5161 "b",633.7439,639.8617,639.222 "c",634.3753,636.4083,641.4688 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",49.9653,49.8576,49.8637 "b",50.4754,49.9939,50.0432 "c",50.4259,50.2659,49.8675 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",189.0949,185.2259,183.7563 "b",189.9041,188.01,187.6986 "c",188.6862,187.4128,188.5983 "Neural Magic DeepSparse 1.6 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",5.2847,5.3952,5.4389 "b",5.2622,5.3154,5.324 "c",5.2963,5.3324,5.2988 "Neural Magic DeepSparse 1.6 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",95.9636,96.6987,95.7407 "b",95.9041,95.0918,95.9029 "c",97.012,96.8029,96.7415 "Neural Magic DeepSparse 1.6 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",333.3922,330.8599,334.1668 "b",333.6033,335.7337,333.6089 "c",329.7906,330.502,330.7129 "Neural Magic DeepSparse 1.6 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",35.2889,35.2266,34.7915 "b",34.5664,34.0391,35.2466 "c",35.0078,31.554,34.9355,34.7356,35.0892,32.5942,31.2612,34.938,34.2057,34.68,34.6931,34.942,31.8183,33.3477,32.0663 "Neural Magic DeepSparse 1.6 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",28.3123,28.3616,28.7095 "b",28.9005,29.3462,28.3496 "c",28.5412,31.6711,28.5959,28.7637,28.4783,30.6564,31.9671,28.5972,29.2063,28.8095,28.7995,28.5908,31.3988,29.9613,31.1618 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",937.5079,938.0061,938.6842 "b",937.7604,937.5166,937.4554 "c",937.7644,937.8175,938.007 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",34.094,34.0716,34.0519 "b",34.0854,34.089,34.0972 "c",34.0852,34.0783,34.074 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",67.5119,68.3895,67.7068 "b",68.209,68.3666,67.9524 "c",67.4755,67.4666,67.7984 "Neural Magic DeepSparse 1.6 - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",14.805,14.6151,14.7627 "b",14.6543,14.6201,14.7092 "c",14.8123,14.8148,14.7424 "Neural Magic DeepSparse 1.6 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",71.8569,72.3861,71.8956 "b",72.0256,72.0774,72.1595 "c",71.6399,71.8823,71.826 "Neural Magic DeepSparse 1.6 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",443.4997,440.9816,442.1817 "b",442.6541,440.8599,440.9189 "c",443.6589,442.9842,442.8316 "Neural Magic DeepSparse 1.6 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream", Higher Results Are Better "a",34.5328,34.6314,34.6635 "b",34.5966,34.6706,34.6079 "c",34.3981,34.451,34.5088 "Neural Magic DeepSparse 1.6 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream", Lower Results Are Better "a",28.9528,28.8704,28.8439 "b",28.8995,28.8376,28.8896 "c",29.0666,29.0214,28.9734