sdfa

AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 23.10 via the Phoronix Test Suite.

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  Test
  Duration
a
December 11 2023
  22 Hours, 44 Minutes
b
December 12 2023
  7 Hours, 14 Minutes
c
December 12 2023
  21 Hours, 52 Minutes
d
December 12 2023
  21 Hours, 47 Minutes
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  18 Hours, 24 Minutes

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sdfa AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 23.10 via the Phoronix Test Suite. ,,"a","b","c","d" Processor,,AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads),AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads),AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads),AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads) Motherboard,,Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS),Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS),Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS),Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) Chipset,,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse Memory,,128GB,128GB,128GB,128GB Disk,,Samsung SSD 970 EVO Plus 500GB,Samsung SSD 970 EVO Plus 500GB,Samsung SSD 970 EVO Plus 500GB,Samsung SSD 970 EVO Plus 500GB Graphics,,AMD Radeon RX 5700 8GB (1750/875MHz),AMD Radeon RX 5700 8GB (1750/875MHz),AMD Radeon RX 5700 8GB (1750/875MHz),AMD Radeon RX 5700 8GB (1750/875MHz) Audio,,AMD Navi 10 HDMI Audio,AMD Navi 10 HDMI Audio,AMD Navi 10 HDMI Audio,AMD Navi 10 HDMI Audio Monitor,,DELL P2415Q,DELL P2415Q,DELL P2415Q,DELL P2415Q Network,,Intel I211 + Intel Wi-Fi 6 AX200,Intel I211 + Intel Wi-Fi 6 AX200,Intel I211 + Intel Wi-Fi 6 AX200,Intel I211 + Intel Wi-Fi 6 AX200 OS,,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10 Kernel,,6.5.0-13-generic (x86_64),6.5.0-13-generic (x86_64),6.5.0-13-generic (x86_64),6.5.0-13-generic (x86_64) Desktop,,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0 Display Server,,X Server + Wayland,X Server + Wayland,X Server + Wayland,X Server + Wayland OpenGL,,4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54),4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54),4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54),4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54) Compiler,,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0 File-System,,ext4,ext4,ext4,ext4 Screen Resolution,,3840x2160,3840x2160,3840x2160,3840x2160 ,,"a","b","c","d" "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,37.9294,39.3833,37.7845,38.7188 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,13.8987,14.4029,13.8813,13.9020 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,980.4497,993.6037,988.4905,989.0589 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,129.7041,131.167,132.1047,134.3975 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,441.4407,450.8062,445.1623,441.3941 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (items/sec)",HIB,103.5643,106.9295,106.0333,103.9791 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2555.4232,2635.5729,2548.3771,2543.1138 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,627.7539,599.1863,591.2570,620.2412 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,201.9130,206.9627,199.2162,201.9444 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,86.3769,88.165,87.9306,87.4654 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,49.2180,49.3328,49.0805,49.1687 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (items/sec)",HIB,11.3088,11.6057,11.8387,11.7423 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,449.3079,448.7603,452.0401,450.0598 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,106.4432,106.5387,107.1042,104.2930 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,215.8297,212.7552,216.3914,215.2909 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,91.1432,89.8018,91.1565,89.5918 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,336.1917,337.0821,337.7813,335.0968 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,56.7902,59.0082,57.1793,56.8599 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,43.1906,43.8384,43.0454,43.0569 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (items/sec)",HIB,17.0745,17.9912,16.9865,17.0878 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,503.4132,508.5902,506.1330,504.8420 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,64.7072,64.3985,64.1154,64.0842 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,37.7351,37.9456,37.9380,37.4534 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,14.0751,14.3078,14.1048,13.9997 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,836.9172,806.3928,841.3435,820.1208 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,71.9375,69.4174,72.0273,71.9192 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,32.6019,32.1567,32.3392,32.3108 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,7.7066,7.6192,7.5689,7.4402 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,72.4193,70.9424,71.8091,72.4572 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (ms/batch)",LIB,9.6462,9.3424,9.4215,9.6084 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,12.4868,12.1095,12.5199,12.5483 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,1.5897,1.6656,1.6887,1.6090 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,158.1544,154.3035,160.2780,158.1065 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,11.5611,11.3279,11.3576,11.4172 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,649.9348,648.524,649.7550,650.6931 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (ms/batch)",LIB,88.4675,86.1505,84.4587,85.1572 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,71.1719,71.2672,70.7399,71.0506 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,9.3853,9.377,9.3277,9.5802 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,147.9620,150.2259,147.4889,148.2827 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,10.9635,11.1265,10.9619,11.1539 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,95.0151,94.8818,94.6789,95.4458 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,17.5978,16.9355,17.4779,17.5761 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,736.7739,726.2504,737.9777,737.8524 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (ms/batch)",LIB,58.5511,55.5621,58.8526,58.5011 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,63.4770,62.8112,63.1295,63.2965 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,15.4510,15.522,15.5926,15.6001 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,841.4259,837.4581,837.1418,845.4438 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,71.0390,69.8784,70.8989,71.4165 "Apache Spark TPC-H - Scale Factor: 1 - Geometric Mean Of All Queries (sec)",LIB,2.20328734,2.24531415,2.23705911,2.22356446 "Apache Spark TPC-H - Scale Factor: 1 - Q01 (sec)",LIB,4.69511843,4.73092079,4.84034109,4.84622987 "Apache Spark TPC-H - Scale Factor: 1 - Q02 (sec)",LIB,2.19916511,2.20726132,2.27846766,2.27512868 "Apache Spark TPC-H - Scale Factor: 1 - Q03 (sec)",LIB,3.15890259,3.2391243,3.34556897,3.15447322 "Apache Spark TPC-H - Scale Factor: 1 - Q04 (sec)",LIB,2.96026391,3.09257221,2.94428595,2.85856040 "Apache Spark TPC-H - Scale Factor: 1 - Q05 (sec)",LIB,3.46156806,3.3776865,3.52418653,3.30995369 "Apache Spark TPC-H - Scale Factor: 1 - Q06 (sec)",LIB,0.75870752,0.73223764,0.71082556,0.74262398 "Apache Spark TPC-H - Scale Factor: 1 - Q07 (sec)",LIB,3.16296500,3.30348134,3.18430217,3.25330043 "Apache Spark TPC-H - Scale Factor: 1 - Q08 (sec)",LIB,2.29091269,2.32780766,2.35779921,2.22529737 "Apache Spark TPC-H - Scale Factor: 1 - Q09 (sec)",LIB,4.40090740,4.51510048,4.32967218,4.55872504 "Apache Spark TPC-H - Scale Factor: 1 - Q10 (sec)",LIB,2.83789939,3.07959628,3.02914357,3.14210590 "Apache Spark TPC-H - Scale Factor: 1 - Q11 (sec)",LIB,1.30849856,1.36447799,1.28974267,1.29190469 "Apache Spark TPC-H - Scale Factor: 1 - Q12 (sec)",LIB,2.14987269,2.0294199,2.04039538,2.06954416 "Apache Spark TPC-H - Scale Factor: 1 - Q13 (sec)",LIB,1.40058664,1.45866323,1.39991681,1.39225551 "Apache Spark TPC-H - Scale Factor: 1 - Q14 (sec)",LIB,1.83231536,1.78157055,1.83836599,1.83219139 "Apache Spark TPC-H - Scale Factor: 1 - Q15 (sec)",LIB,1.99491587,2.17460775,2.14363774,2.27715731 "Apache Spark TPC-H - Scale Factor: 1 - Q16 (sec)",LIB,1.42731291,1.43939853,1.49448760,1.53928820 "Apache Spark TPC-H - Scale Factor: 1 - Q17 (sec)",LIB,2.66192222,2.72264194,2.58527072,2.57773050 "Apache Spark TPC-H - Scale Factor: 1 - Q18 (sec)",LIB,4.00372249,4.0458951,3.99324067,3.86921136 "Apache Spark TPC-H - Scale Factor: 1 - Q19 (sec)",LIB,1.02847038,1.1739459,1.20837911,0.99435820 "Apache Spark TPC-H - Scale Factor: 1 - Q20 (sec)",LIB,2.75555176,2.58762598,2.75284823,2.74797662 "Apache Spark TPC-H - Scale Factor: 1 - Q21 (sec)",LIB,7.39505470,7.70369244,7.46197589,7.40773551 "Apache Spark TPC-H - Scale Factor: 1 - Q22 (sec)",LIB,1.08502284,0.98886323,1.05880324,1.06113847 "Apache Spark TPC-H - Scale Factor: 10 - Geometric Mean Of All Queries (sec)",LIB,8.17090667,7.89399455,8.11142575,8.24567273 "Apache Spark TPC-H - Scale Factor: 10 - Q01 (sec)",LIB,8.67833742,8.70151806,8.66681448,8.73231697 "Apache Spark TPC-H - Scale Factor: 10 - Q02 (sec)",LIB,4.85099522,4.88495016,4.92897081,4.79437430 "Apache Spark TPC-H - Scale Factor: 10 - Q03 (sec)",LIB,10.24406719,10.32122612,10.26445103,10.15224552 "Apache Spark TPC-H - Scale Factor: 10 - Q04 (sec)",LIB,8.63682970,8.70809078,8.50457668,8.33958340 "Apache Spark TPC-H - Scale Factor: 10 - Q05 (sec)",LIB,12.47607358,12.91888523,12.66337935,12.65661907 "Apache Spark TPC-H - Scale Factor: 10 - Q06 (sec)",LIB,4.40131362,4.62162924,4.30036068,4.36710962 "Apache Spark TPC-H - Scale Factor: 10 - Q07 (sec)",LIB,10.63118744,10.531744,10.62009271,10.74541600 "Apache Spark TPC-H - Scale Factor: 10 - Q08 (sec)",LIB,10.99399408,10.67045593,10.85271359,10.81727695 "Apache Spark TPC-H - Scale Factor: 10 - Q09 (sec)",LIB,14.89943695,14.1802969,14.81898117,14.92097505 "Apache Spark TPC-H - Scale Factor: 10 - Q10 (sec)",LIB,10.26555188,10.18445492,10.41971207,10.35872300 "Apache Spark TPC-H - Scale Factor: 10 - Q11 (sec)",LIB,4.54931625,4.26761341,4.38963429,4.48057460 "Apache Spark TPC-H - Scale Factor: 10 - Q12 (sec)",LIB,8.03465001,8.10859299,8.17116038,8.09419775 "Apache Spark TPC-H - Scale Factor: 10 - Q13 (sec)",LIB,4.45708307,4.03698015,4.09777006,4.61340586 "Apache Spark TPC-H - Scale Factor: 10 - Q14 (sec)",LIB,5.79615275,5.82840872,5.86177413,5.73522472 "Apache Spark TPC-H - Scale Factor: 10 - Q15 (sec)",LIB,5.83709431,5.68089533,5.81021436,5.85565599 "Apache Spark TPC-H - Scale Factor: 10 - Q16 (sec)",LIB,4.32050626,4.15591764,4.17572975,4.34601260 "Apache Spark TPC-H - Scale Factor: 10 - Q17 (sec)",LIB,12.45044740,12.44107723,12.41860390,12.40058359 "Apache Spark TPC-H - Scale Factor: 10 - Q18 (sec)",LIB,14.86223253,14.87680531,16.11452039,14.91129049 "Apache Spark TPC-H - Scale Factor: 10 - Q19 (sec)",LIB,7.21627538,6.0425024,6.54328155,8.02795347 "Apache Spark TPC-H - Scale Factor: 10 - Q20 (sec)",LIB,8.84160964,8.87663841,8.91217136,8.82452583 "Apache Spark TPC-H - Scale Factor: 10 - Q21 (sec)",LIB,29.31493378,28.79863548,29.03367678,28.90806135 "Apache Spark TPC-H - Scale Factor: 10 - Q22 (sec)",LIB,3.53586213,3.40110779,3.69966158,3.59682607 "Apache Spark TPC-H - Scale Factor: 50 - Geometric Mean Of All Queries (sec)",LIB,27.97562823,27.78682893,28.11219413,28.12394226 "Apache Spark TPC-H - Scale Factor: 50 - Q01 (sec)",LIB,26.02234904,25.99035454,26.00166639,26.11903827 "Apache Spark TPC-H - Scale Factor: 50 - Q02 (sec)",LIB,10.48352242,10.45031643,10.56094869,10.44357236 "Apache Spark TPC-H - Scale Factor: 50 - Q03 (sec)",LIB,36.61449941,36.02916718,37.05844625,35.99200439 "Apache Spark TPC-H - Scale Factor: 50 - Q04 (sec)",LIB,30.58487765,30.26870918,30.22341601,30.55707931 "Apache Spark TPC-H - Scale Factor: 50 - Q05 (sec)",LIB,41.16542689,43.25001144,39.70042801,38.99460093 "Apache Spark TPC-H - Scale Factor: 50 - Q06 (sec)",LIB,20.38117282,20.29723358,20.34083811,20.38204702 "Apache Spark TPC-H - Scale Factor: 50 - Q07 (sec)",LIB,35.63054784,35.34214783,35.45530701,35.40038427 "Apache Spark TPC-H - Scale Factor: 50 - Q08 (sec)",LIB,38.35942205,37.97156906,37.80742772,38.38075257 "Apache Spark TPC-H - Scale Factor: 50 - Q09 (sec)",LIB,46.89715449,46.31754303,47.10843913,46.99718602 "Apache Spark TPC-H - Scale Factor: 50 - Q10 (sec)",LIB,35.92603938,36.27207947,36.82142385,35.92824809 "Apache Spark TPC-H - Scale Factor: 50 - Q11 (sec)",LIB,9.06239065,8.69320774,8.75260639,9.01768939 "Apache Spark TPC-H - Scale Factor: 50 - Q12 (sec)",LIB,30.43039259,30.40716553,30.88582865,30.04180272 "Apache Spark TPC-H - Scale Factor: 50 - Q13 (sec)",LIB,12.33711910,12.13110542,13.13648542,13.68457921 "Apache Spark TPC-H - Scale Factor: 50 - Q14 (sec)",LIB,25.48705292,25.39692879,25.45622126,25.42378616 "Apache Spark TPC-H - Scale Factor: 50 - Q15 (sec)",LIB,23.04547437,22.88924599,22.94638952,23.00236766 "Apache Spark TPC-H - Scale Factor: 50 - Q16 (sec)",LIB,10.58654118,10.53230286,10.82443651,10.91404247 "Apache Spark TPC-H - Scale Factor: 50 - Q17 (sec)",LIB,55.60917791,55.27999115,55.33429082,55.42181269 "Apache Spark TPC-H - Scale Factor: 50 - Q18 (sec)",LIB,62.50857417,61.9550209,62.29955419,62.73364003 "Apache Spark TPC-H - Scale Factor: 50 - Q19 (sec)",LIB,24.71872266,25.07553101,24.89447530,25.02892049 "Apache Spark TPC-H - Scale Factor: 50 - Q20 (sec)",LIB,30.70769501,30.53813362,30.78961944,30.51781400 "Apache Spark TPC-H - Scale Factor: 50 - Q21 (sec)",LIB,130.86564128,131.45526123,131.42175293,131.00612386 "Apache Spark TPC-H - Scale Factor: 50 - Q22 (sec)",LIB,10.67486382,10.52690792,10.63667170,10.26505438 "Apache Spark TPC-H - Scale Factor: 100 (sec)",LIB,,,,