amazon testing on Ubuntu 22.04 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 2310055-NE-2310039NE76
GCE c3d-standard-60,
"OpenVINO 2023.1 - Model: Face Detection FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",35.17,35.22,35.17
"t2d-standard-60 AMD Milan",26.27,26.31,26.25
"c6g.16xlarge",0.04,0.04,0.04
"OpenVINO 2023.1 - Model: Weld Porosity Detection FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",15.98,15.97,15.98
"t2d-standard-60 AMD Milan",14.74,14.76,14.77
"c6g.16xlarge",119.23,119.04,119.25
"OpenSSL 3.1 - Algorithm: RSA4096",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",20101.4,20051.8,20085.4
"t2d-standard-60 AMD Milan",12994.1,12970.6,12954.2
"c6g.16xlarge",2639.8,2640.1,2640
"OpenVINO 2023.1 - Model: Weld Porosity Detection FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",3644.95,3656.3,3650.46
"t2d-standard-60 AMD Milan",2640.38,2651.41,2647.96
"c6g.16xlarge",5.49,5.49,5.51
"OpenVINO 2023.1 - Model: Face Detection FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",340.58,339.88,340.42
"t2d-standard-60 AMD Milan",568.69,568.2,569.42
"c6g.16xlarge",22371.66,22422.55,22381.38
"OpenVINO 2023.1 - Model: Face Detection Retail FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",4.52,4.54,4.53
"t2d-standard-60 AMD Milan",3.52,3.52,3.52
"c6g.16xlarge",2230.56,2193.21,2136.67
"NAS Parallel Benchmarks 3.4 - Test / Class: BT.C",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",96031.29,96450.87,96290.29
"t2d-standard-60 AMD Milan",122801.16,122655.41,122705.25
"c6g.16xlarge",24239.43,24214.1,24233.88
"OpenVINO 2023.1 - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",647.21,644.52,645.5
"t2d-standard-60 AMD Milan",565.5,564.63,565.9
"c6g.16xlarge",0.15,0.15,0.15
"OpenVINO 2023.1 - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",55008.84,54880.77,55024.16
"t2d-standard-60 AMD Milan",43415.23,44542.58,44189.65
"c6g.16xlarge",136.32,135.26,136.9
"NAS Parallel Benchmarks 3.4 - Test / Class: SP.C",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",39831.19,39949.73,39978.2
"t2d-standard-60 AMD Milan",43815.03,43752.43,42116.86
"c6g.16xlarge",9717.22,9718.18,9715.57
"libavif avifenc 1.0 - Encoder Speed: 2",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",41.419,41.447,41.749
"t2d-standard-60 AMD Milan",41.983,41.941,42.042
"c6g.16xlarge",168.383,167.739,167.716
"OpenVINO 2023.1 - Model: Handwritten English Recognition FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",964.31,963.5,965.57
"t2d-standard-60 AMD Milan",370.94,368.12,371.04
"c6g.16xlarge",2.55,2.5,2.54
"OpenVINO 2023.1 - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",18.52,18.59,18.57
"t2d-standard-60 AMD Milan",26.49,26.53,26.47
"c6g.16xlarge",6855.37,6619.53,6845.02
"OpenVINO 2023.1 - Model: Handwritten English Recognition FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",758.9,759.93,764.58
"t2d-standard-60 AMD Milan",392.35,387.99,391.83
"c6g.16xlarge",2.36,2.36,2.36
"OpenSSL 3.1 - Algorithm: RSA4096",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",493110.5,493144.6,492977.7
"t2d-standard-60 AMD Milan",861892.7,859670.9,860970.2
"c6g.16xlarge",215693.2,215670.9,215685.6
"libavif avifenc 1.0 - Encoder Speed: 0",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",78.181,77.941,78.083
"t2d-standard-60 AMD Milan",78.512,78.28,78.257
"c6g.16xlarge",270.579,269.436,270.189
"TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",69.66,69.81,69.57
"t2d-standard-60 AMD Milan",20.85,20.94,20.91
"c6g.16xlarge",
"TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",62.84,62.84,62.55
"t2d-standard-60 AMD Milan",20.47,20.25,20.36
"c6g.16xlarge",
"Timed Linux Kernel Compilation 6.1 - Build: defconfig",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",34.87,32.981,33.053,33.085,33.007
"c6g.16xlarge",103.849,101.406,101.392
"OpenVINO 2023.1 - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",43593.45,43643.5,43584.18
"t2d-standard-60 AMD Milan",29641.49,29671.67,29691.19
"c6g.16xlarge",179.26,178.05,179.16
"OpenVINO 2023.1 - Model: Person Vehicle Bike Detection FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",1771.62,1756.45,1764.55
"t2d-standard-60 AMD Milan",632.73,640.55,627.99
"c6g.16xlarge",7.38,7.34,7.37
"OpenVINO 2023.1 - Model: Weld Porosity Detection FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",1875.24,1876.11,1874.48
"t2d-standard-60 AMD Milan",1015.81,1014.31,1013.98
"c6g.16xlarge",8.39,8.4,8.38
"OpenVINO 2023.1 - Model: Road Segmentation ADAS FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",578.62,577.18,575.03
"t2d-standard-60 AMD Milan",227.11,225.43,223.89
"c6g.16xlarge",2.61,2.62,2.61
"OpenVINO 2023.1 - Model: Weld Porosity Detection FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",8.22,8.19,8.2
"t2d-standard-60 AMD Milan",11.34,11.3,11.31
"c6g.16xlarge",182.08,182.27,181.46
"OpenVINO 2023.1 - Model: Vehicle Detection FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",1388.58,1401.18,1379.32
"t2d-standard-60 AMD Milan",371.49,366.65,367.03
"c6g.16xlarge",6.52,6.53,6.54
"OpenVINO 2023.1 - Model: Face Detection Retail FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",4180.76,4150.59,4167.82
"t2d-standard-60 AMD Milan",1295.8,1254.15,1306.47
"c6g.16xlarge",20.8,20.77,20.8
"OpenVINO 2023.1 - Model: Person Vehicle Bike Detection FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",6.76,6.82,6.79
"t2d-standard-60 AMD Milan",23.68,23.39,23.86
"c6g.16xlarge",135.56,136.28,135.76
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",50.96,51.07,50.94
"t2d-standard-60 AMD Milan",18.35,18.33,18.2
"c6g.16xlarge",
"OpenSSL 3.1 - Algorithm: ChaCha20",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",173997876570,173956964900,173988008210
"t2d-standard-60 AMD Milan",180329677620,180253168070,180164591620
"c6g.16xlarge",67324185260,67325465120,67324684700
"OpenSSL 3.1 - Algorithm: ChaCha20-Poly1305",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",123910223190,123902548100,123915143030
"t2d-standard-60 AMD Milan",119772086820,119912340960,119258733230
"c6g.16xlarge",46716242330,46718360780,46710776350
"NAS Parallel Benchmarks 3.4 - Test / Class: FT.C",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",44801.35,38283.73,38604.18,38579.43,38290.5,38171.82,38324.3,39689.55,38589.61,38372.77,38742.02,38527.85,44012.9,38370.63,43351.46
"t2d-standard-60 AMD Milan",54635.02,55105.07,54798.44
"c6g.16xlarge",21387.39,21381,21390.73
"OpenSSL 3.1 - Algorithm: AES-256-GCM",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",293316072260,293211079750,293456993480
"t2d-standard-60 AMD Milan",216309338390,215696831010,216071733520
"c6g.16xlarge",129194047620,129199709390,129200835790
"NAS Parallel Benchmarks 3.4 - Test / Class: EP.D",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",3815.81,3812.71,3722.29
"t2d-standard-60 AMD Milan",4735,5011.74,4957.32,5004.77,4969.57
"c6g.16xlarge",2228.23,2207.93,2205.13
"OpenSSL 3.1 - Algorithm: AES-128-GCM",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",342460098150,343637034330,343188720840
"t2d-standard-60 AMD Milan",235112254400,234831738740,233868254690
"c6g.16xlarge",158781697500,158799480150,158784355260
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency",
Lower Results Are Better
"t2d-standard-60 AMD Milan",0.49,0.509,0.496
"c6g.16xlarge",1.047,1.029,1.002
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 1000 - Mode: Read Only",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",2042646.567188,1965900.775193,2016011.067664
"c6g.16xlarge",955053.130528,971700.089933,998339.41324
"Remhos 1.0 - Test: Sample Remap Example",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",33.691,33.166,33.228
"t2d-standard-60 AMD Milan",16.414,16.238,16.326
"c6g.16xlarge",20.76,20.904,20.785
"OpenVINO 2023.1 - Model: Face Detection FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",18.4,18.39,18.38
"t2d-standard-60 AMD Milan",10.72,10.74,10.72
"c6g.16xlarge",0.1,0.1,0.1
"OpenVINO 2023.1 - Model: Road Segmentation ADAS FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",20.71,20.76,20.84
"t2d-standard-60 AMD Milan",65.98,66.48,66.93
"c6g.16xlarge",382.44,382.15,382.83
"OpenVINO 2023.1 - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",0.4,0.4,0.4
"t2d-standard-60 AMD Milan",0.6,0.61,0.61
"c6g.16xlarge",7.32,7.38,7.29
"OpenVINO 2023.1 - Model: Vehicle Detection FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",8.62,8.55,8.68
"t2d-standard-60 AMD Milan",40.33,40.86,40.82
"c6g.16xlarge",153.29,153.07,152.99
"OpenVINO 2023.1 - Model: Face Detection Retail FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",2.86,2.88,2.87
"t2d-standard-60 AMD Milan",11.55,11.93,11.46
"c6g.16xlarge",48.06,48.13,48.06
"OpenVINO 2023.1 - Model: Face Detection FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",648.53,648.77,649.12
"t2d-standard-60 AMD Milan",1395.09,1390.92,1394.66
"c6g.16xlarge",9997.39,9994.54,9997.76
"OpenVINO 2023.1 - Model: Vehicle Detection FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",2048.81,2037.92,2042.42
"t2d-standard-60 AMD Milan",1512.54,1514.53,1510.65
"c6g.16xlarge",0.15,0.14,0.14,0.14,0.14,0.15,0.14,0.15,0.14,0.14,0.15,0.14,0.14,0.14,0.14
"OpenVINO 2023.1 - Model: Face Detection Retail FP16-INT8 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",6613.67,6592.31,6609.37
"t2d-standard-60 AMD Milan",4243.67,4237.32,4237.56
"c6g.16xlarge",0.45,0.46,0.47
"OpenVINO 2023.1 - Model: Machine Translation EN To DE FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",184.93,185.76,185.19
"t2d-standard-60 AMD Milan",95.94,96.59,97.21
"c6g.16xlarge",1.36,1.36,1.36
"OpenVINO 2023.1 - Model: Handwritten English Recognition FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",31.09,31.11,31.04
"t2d-standard-60 AMD Milan",80.81,81.42,80.78
"c6g.16xlarge",392.48,399.29,393.04
"OpenVINO 2023.1 - Model: Vehicle Detection FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",5.84,5.87,5.86
"t2d-standard-60 AMD Milan",9.9,9.89,9.91
"c6g.16xlarge",6846.14,7080.71,6962.15,7082.83,7082.83,6846.73,6908.41,6846.49,7081.92,7087.18,6845.86,7064.54,7062.9,6966.15,7086.59
"OpenVINO 2023.1 - Model: Machine Translation EN To DE FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",64.84,64.54,64.73
"t2d-standard-60 AMD Milan",156.17,155.11,154.15
"c6g.16xlarge",735.09,735.98,735.66
"OpenVINO 2023.1 - Model: Handwritten English Recognition FP16-INT8 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",39.5,39.44,39.2
"t2d-standard-60 AMD Milan",76.39,77.26,76.5
"c6g.16xlarge",423.43,424.15,424.27
"OpenVINO 2023.1 - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",0.52,0.52,0.52
"t2d-standard-60 AMD Milan",0.99,0.99,0.99
"c6g.16xlarge",5.57,5.61,5.57
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency",
Lower Results Are Better
"t2d-standard-60 AMD Milan",0.404,0.391,0.403
"c6g.16xlarge",0.785,0.759,0.757
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 800 - Mode: Read Only",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",1982417.571961,2044890.994463,1984043.124925
"c6g.16xlarge",1019179.317733,1054298.726273,1056324.429941
"GROMACS 2023 - Implementation: MPI CPU - Input: water_GMX50_bare",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",4.41,4.392,4.372
"t2d-standard-60 AMD Milan",5.296,5.291,5.28
"c6g.16xlarge",2.766,2.768,2.764
"NAS Parallel Benchmarks 3.4 - Test / Class: MG.C",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",42753.02,42702.29,42650.19
"t2d-standard-60 AMD Milan",47040.34,47542.83,47292.7
"c6g.16xlarge",25642.24,25660.56,25680.31
"Rodinia 3.1 - Test: OpenMP CFD Solver",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",10.002,10.048,10.025
"t2d-standard-60 AMD Milan",7.3,7.403,7.402
"c6g.16xlarge",5.98,5.983,5.985
"OpenSSL 3.1 - Algorithm: SHA512",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",14706676460,14693471250,14706664010
"t2d-standard-60 AMD Milan",22344453570,22361481200,22028477780
"c6g.16xlarge",14391682440,14390565740,14372505410
"Timed Node.js Compilation 19.8.1 - Time To Compile",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",198.042,198.181,198.959
"t2d-standard-60 AMD Milan",191.785,191.728,191.605
"c6g.16xlarge",286.258,285.986,286.36
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",89.1779,89.1183,87.5941
"t2d-standard-60 AMD Milan",108.11,110.474,110.444
"c6g.16xlarge",129.365,128.993,129.159
"Laghos 3.1 - Test: Sedov Blast Wave, ube_922_hex.mesh",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",259.1484487662,259.3422599126,260.1462481379
"t2d-standard-60 AMD Milan",364.8337897952,363.481897713,365.5954447435
"c6g.16xlarge",322.699229273,321.2045546456,319.9784478035
"libavif avifenc 1.0 - Encoder Speed: 6",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",3.263,3.24,3.248
"t2d-standard-60 AMD Milan",3.194,3.23,3.191
"c6g.16xlarge",4.449,4.495,4.458
"Coremark 1.0 - CoreMark Size 666 - Iterations Per Second",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",1446218.740585,1443435.376195,1447876.447876
"t2d-standard-60 AMD Milan",1748633.879781,1718336.077898,1725005.390642
"c6g.16xlarge",1258603.73648,1260421.453423,1260586.960804
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",144.595,138.044,143.995,154.116,150.529,142.335,147.048,161.921,141.967,143.782,154.982,159.587
"t2d-standard-60 AMD Milan",197.062,195.473,198.308
"c6g.16xlarge",201.486,203.466,202.382
"LAMMPS Molecular Dynamics Simulator 23Jun2022 - Model: 20k Atoms",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",19.763,19.715,19.849
"t2d-standard-60 AMD Milan",26.831,26.696,26.675
"c6g.16xlarge",24.914,25.087,25.177
"Timed Gem5 Compilation 21.2 - Time To Compile",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",176.659,176.742,176.9
"t2d-standard-60 AMD Milan",171.461,170.776,170.554
"c6g.16xlarge",224.381,224.378,224.483
"libavif avifenc 1.0 - Encoder Speed: 6, Lossless",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",7.086,6.793,6.787
"t2d-standard-60 AMD Milan",7.7,7.623,7.595
"c6g.16xlarge",8.851,8.943,8.843
"Rodinia 3.1 - Test: OpenMP LavaMD",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",64.529,65.164,64.893
"t2d-standard-60 AMD Milan",51.12,51.078,50.723
"c6g.16xlarge",62.354,62.253,62.297
"Laghos 3.1 - Test: Triple Point Problem",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",208.5881274533,209.0476809746,209.3606263868
"t2d-standard-60 AMD Milan",218.8283787586,223.4644406484,224.6074011662
"c6g.16xlarge",178.7770936109,179.3027924498,180.4793840112
"BRL-CAD 7.36 - VGR Performance Metric",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",
"c6g.16xlarge",
"Timed Linux Kernel Compilation 6.1 - Build: allmodconfig",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",335.757,332.12,332.175
"c6g.16xlarge",413.89,407.139,406.263
"libxsmm 2-1.17-3645 - M N K: 32",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",255.8,255.2,255.3
"t2d-standard-60 AMD Milan",278.4,292.7,293.4,292.2
"c6g.16xlarge",312.8,313.4,311.8
"Apache Cassandra 4.1.3 - Test: Writes",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",230856,227909,227154
"t2d-standard-60 AMD Milan",188310,187245,185952
"c6g.16xlarge",230058,226129,201769,189461,218116,222524,221884,219760,222002,220874,213004,222679
"libxsmm 2-1.17-3645 - M N K: 64",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",489.8,489.5,489.9
"t2d-standard-60 AMD Milan",553.7,554.5,554.4
"c6g.16xlarge",589.3,587.9,591.2
"OpenSSL 3.1 - Algorithm: SHA256",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",46207306920,46197984480,46230172540
"t2d-standard-60 AMD Milan",50907911600,50844113450,50902966260
"c6g.16xlarge",41904076360,42485113330,42476352230
"7-Zip Compression 22.01 - Test: Compression Rating",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",272103,271103,272178
"t2d-standard-60 AMD Milan",278561,279750,278608
"c6g.16xlarge",239263,239501,240442
"nginx 1.23.2 - Connections: 1000",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",180829.49,181558,179226.04
"t2d-standard-60 AMD Milan",155660.09,155850.64,155316.39
"c6g.16xlarge",158917.94,158721.79,158461.36
"nginx 1.23.2 - Connections: 500",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",187402.16,187110.72,187538.43
"t2d-standard-60 AMD Milan",163037.25,163598.21,162237.8
"c6g.16xlarge",162922.48,162659.65,162079.43
"Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 193 Cells Per Direction",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",28.229826,27.5303421,28.2988949
"t2d-standard-60 AMD Milan",24.1948948,24.2332325,23.1163635,23.094944,23.0567513,26.45327,25.1549797,25.2942066,25.258707,24.7013645,25.0583038,25.2483997
"c6g.16xlarge",25.8534412,25.9035492,25.8675079
"Algebraic Multi-Grid Benchmark 1.2 - ",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",965306900,964571900,958790700
"t2d-standard-60 AMD Milan",922589800,919562400,919131100
"c6g.16xlarge",1032806000,1033233000,1032642000
"7-Zip Compression 22.01 - Test: Decompression Rating",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",226008,225430,227194
"t2d-standard-60 AMD Milan",247380,246600,247785
"c6g.16xlarge",234073,234129,233936
"Rodinia 3.1 - Test: OpenMP Leukocyte",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",45.529,45.782,45.182
"t2d-standard-60 AMD Milan",42.054,42.003,41.974
"c6g.16xlarge",
"Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 129 Cells Per Direction",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",5.83421278,5.97003889,5.81048489
"t2d-standard-60 AMD Milan",5.67420578,5.61493206,5.60258198
"c6g.16xlarge",5.5811429,5.62991381,5.64329386
"OpenRadioss 2023.09.15 - Model: Chrysler Neon 1M",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",341.75,335.91,335.43
"t2d-standard-60 AMD Milan",324.94,329,329.69
"Apache IoTDB 1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",623.72,629.48,618.47
"t2d-standard-60 AMD Milan",622.18,619.85,658.71
"c6g.16xlarge",
"Apache IoTDB 1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",415.5,422.71,417.55
"t2d-standard-60 AMD Milan",407.11,417.51,420.62
"c6g.16xlarge",
"Apache IoTDB 1.2 - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",34831565.91,35554973.9,35693112.85
"t2d-standard-60 AMD Milan",34680351.11,35777328.86,34747992.42
"c6g.16xlarge",
"Apache IoTDB 1.2 - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",34391422.73,34405919.84,34199369.37
"t2d-standard-60 AMD Milan",34208501.63,34295426.94,33867500.37
"c6g.16xlarge",
"Apache IoTDB 1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",33181023.05,33568624.3,33054825.84
"t2d-standard-60 AMD Milan",33745043.74,32860342.37,33795025.28
"c6g.16xlarge",
"Apache IoTDB 1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",35129702.06,34503885.42,34654106.75
"t2d-standard-60 AMD Milan",34500639.54,35243586.87,35033470.97
"c6g.16xlarge",
"Blender 3.6 - Blend File: Pabellon Barcelona - Compute: CPU-Only",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",112.69,112.61,112.62
"Blender 3.6 - Blend File: Barbershop - Compute: CPU-Only",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",351.47,352.68,350.6
"Blender 3.6 - Blend File: Fishy Cat - Compute: CPU-Only",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",45.03,45.46,45.16
"Blender 3.6 - Blend File: Classroom - Compute: CPU-Only",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",89.49,89.28,89.29
"Blender 3.6 - Blend File: BMW27 - Compute: CPU-Only",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",34.38,34.24,34.19
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency",
Lower Results Are Better
"t2d-standard-60 AMD Milan",171.86,177.156,163.46,174.067,174.065,174.374,172.361,174.389
"c6g.16xlarge",195.217,194.597,212.009,219.326,202.615,215.887,209.159,195.004,251.66
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency",
Lower Results Are Better
"t2d-standard-60 AMD Milan",133.617,147.849,146.813,142.139,144.162,139.613,137.77,144.517,140.35,138.569,137.379,138.215
"c6g.16xlarge",152.266,168.646,181.767,192.317,173.855,176.828,177.442,153.309,167.4,152.138,170.158,152.165
"OpenVINO 2023.1 - Model: Person Detection FP32 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",83.89,84.42,83.42
"t2d-standard-60 AMD Milan",196.06,200.35,241.48,172.35,173.24,235.71,204.63,171,172.97,171.62,171.95,174.46,172.66,180.47,262.74
"c6g.16xlarge",947.13,947.52,948.94
"OpenVINO 2023.1 - Model: Person Detection FP32 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",142.92,142.05,143.72
"t2d-standard-60 AMD Milan",76.46,74.7,62.04,86.9,86.49,63.51,73.19,87.6,86.64,87.28,87.1,85.86,86.8,82.92,56.98
"c6g.16xlarge",1.06,1.06,1.05
"OpenVINO 2023.1 - Model: Person Detection FP16 - Device: CPU",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",83.77,84.23,83.96
"t2d-standard-60 AMD Milan",171.31,169.06,262.99,187.39,208,228.03,172.17,261.46,179.1,223.04,216.44,182.06,262.43,170.56,232.97
"c6g.16xlarge",947.35,947.11,948.31
"OpenVINO 2023.1 - Model: Person Detection FP16 - Device: CPU",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",143.12,142.34,142.79
"t2d-standard-60 AMD Milan",87.4,88.62,56.94,79.95,71.99,65.7,87,57.29,83.64,67.1,69.22,82.19,57.02,87.8,64.25
"c6g.16xlarge",1.06,1.06,1.05
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 1000 - Mode: Read Write",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",5818.693795,5644.7456,6117.687064,5744.902176,5744.991347,5734.792615,5801.772905,5734.319626
"c6g.16xlarge",5122.505864,5138.815024,4716.77393,4559.419355,4935.457071,4632.060402,4781.05152,5128.109479,3973.608002
"PostgreSQL 16 - Scaling Factor: 100 - Clients: 800 - Mode: Read Write",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",5987.245077,5410.928583,5449.106271,5628.296483,5549.305545,5730.131143,5806.791885,5535.686673,5700.035112,5773.278611,5823.319161,5788.084243
"c6g.16xlarge",5253.958834,4743.67018,4401.227478,4159.807754,4601.547889,4524.171776,4508.505785,5218.221526,4778.975141,5258.391273,4701.509436,5257.451089
"Apache IoTDB 1.2 - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",687.68,691.46,667.23
"t2d-standard-60 AMD Milan",703.63,667.86,756.89
"c6g.16xlarge",
"Apache IoTDB 1.2 - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",480.18,468.96,393.9
"t2d-standard-60 AMD Milan",371.9,495.11,434.88
"c6g.16xlarge",
"Stockfish 15 - Total Time",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",106759554,103063203,107860613
"t2d-standard-60 AMD Milan",119578499,111838439,117494314,117271976,105695810,104784270,114810498,112987323,124362514,117936702,112757559,110100145,107750006,104054980
"c6g.16xlarge",91243465,84350638,79341255,72392522,75777208,91234800,79080385,82577470,93109816,86653807,77058316,75088095,82095342,80119372,76993095
"LAMMPS Molecular Dynamics Simulator 23Jun2022 - Model: Rhodopsin Protein",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",17.435,17.943,18.782,15.397,16.136,19.091,19.469,19.611,15.494,19.436,15.147,15.137
"t2d-standard-60 AMD Milan",28.031,27.485,27.969
"c6g.16xlarge",26.048,26.111,25.963
"nekRS 23.0 - Input: TurboPipe Periodic",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",3968650000,5286380000,3966870000,5280290000,5298140000,3888790000,3949880000,5290710000,5317680000,5262920000,5290660000,3886310000
"t2d-standard-60 AMD Milan",2729670000,2730960000,2731230000
"c6g.16xlarge",2224530000,2218390000,2222210000
"nekRS 23.0 - Input: Kershaw",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",4055310000,4105940000,4420360000,4373160000,3970840000,4468840000,3982360000,4398690000,4449770000,4466570000,4412340000,4374120000
"t2d-standard-60 AMD Milan",3818020000,2808430000,3826890000,3821550000,3803790000,3690990000,3835140000,3801950000,3663420000,3495520000,3868600000,3748930000
"c6g.16xlarge",1755880000,1764800000,1755900000
"OpenRadioss 2023.09.15 - Model: INIVOL and Fluid Structure Interaction Drop Container",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",
"t2d-standard-60 AMD Milan",
"OpenRadioss 2023.09.15 - Model: Rubber O-Ring Seal Installation",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",101.97,98.1,93.92,87.07,95.09,96.96,99.34,82.92,62.54,61.88,97.16,98.89
"t2d-standard-60 AMD Milan",72.16,72.37,71.64
"OpenRadioss 2023.09.15 - Model: Bird Strike on Windshield",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",138.37,135.81,145.2,143.18,153.03,152.12,168.83,144.64,144.64
"t2d-standard-60 AMD Milan",123.87,123.52,123.45
"OpenRadioss 2023.09.15 - Model: Cell Phone Drop Test",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",48.81,35.18,47.32,36.54,35.41,35.4,35.28,35.31,35.33,42.45,35.41,35.27,41.19,38.01,45.36
"t2d-standard-60 AMD Milan",34.2,33.4,29.32,29.72,29.71,29.5,29.55,29.33,29.39,29.67,29.79,29.82,29.38,29.63,29.39
"OpenRadioss 2023.09.15 - Model: Bumper Beam",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",92.33,100.2,91.64,91.89,90.46,92.63,91.75,88.48,91.56,112.18,87.28,89.62,91.92,90.55,90.54
"t2d-standard-60 AMD Milan",75.53,75.87,75.63
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",95.9282,95.3365,88.9761,90.101,95.3498,91.278,99.678,107.974,83.7966,94.0245,92.0231,88.7398
"t2d-standard-60 AMD Milan",107.51,106.19,104.386
"c6g.16xlarge",79.5113,79.9184,77.6171
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",62.7598,46.0513,58.3489,48.9808,62.8683,55.6972,58.2967,63.0399,54.9577,55.8532,62.817,54.8017,59.9014,59.0128,56.2873
"t2d-standard-60 AMD Milan",60.858,58.7287,60.5162
"c6g.16xlarge",32.217,32.5611,32.2945
"Rodinia 3.1 - Test: OpenMP Streamcluster",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",6.914,6.902,6.155,6.112,6.975,6.116,6.152,6.906,6.165,6.911,6.935,6.09,6.087,6.147,6.146
"t2d-standard-60 AMD Milan",6.428,6.406,6.435
"c6g.16xlarge",14.245,14.197,14.193
"Rodinia 3.1 - Test: OpenMP HotSpot3D",
Lower Results Are Better
"c3d-standard-60 AMD Genoa",88.784,86.666,80.112,86.692,86.284,82.528,80.032,86.448,87.133,80.077,83.267,87.391,86.852,80.156,80.066
"t2d-standard-60 AMD Milan",93.108,88.525,94.42,94.761,82.549,94.56,94.73,81.874,81.513,94.162,81.105,81.11
"c6g.16xlarge",
"NAS Parallel Benchmarks 3.4 - Test / Class: LU.C",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",72978.56,73807.85,73902.98
"t2d-standard-60 AMD Milan",74972.59,89154.93,95667.8,96417.39,96482.45,95714.04,96488.77,94153.61,96894.72,96941.08,96186.26,95766.41,95701.78,96440.4,96734.37
"c6g.16xlarge",18805.92,18821.59,18795.75
"NAS Parallel Benchmarks 3.4 - Test / Class: IS.D",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",2375.98,2643.98,2353.5,2292.48,2353.61,2361.23,2686.31,2271.09,2642.74,2362.39,2598.16,2356.89,2341.14,2356.29,2340.19
"t2d-standard-60 AMD Milan",2278.16,2293.11,1660.62,1268.64,1267.65,1275.23,1265.34,1545.24,2341.41,2276.57,2283.55,1275.95
"c6g.16xlarge",916.8,914.79,915.8
"NAS Parallel Benchmarks 3.4 - Test / Class: CG.C",
Higher Results Are Better
"c3d-standard-60 AMD Genoa",19723.53,19614.86,19455.2
"t2d-standard-60 AMD Milan",19637.23,9101.22,9077.23,9154.03,9202.98,19071.14,19770.57,19188.18,19316.74,20064.88,19237.95,19764.05,18817.05,18485.91,19851.46
"c6g.16xlarge",13333.72,13308.3,13388.04