Tests for a future article. AMD EPYC 9124 16-Core testing with a Supermicro H13SSW (1.1 BIOS) and astdrmfb on AlmaLinux 9.2 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 2310228-NE-EXTRATEST37
extra tests2
Tests for a future article. AMD EPYC 9124 16-Core testing with a Supermicro H13SSW (1.1 BIOS) and astdrmfb on AlmaLinux 9.2 via the Phoronix Test Suite.
,,"a","b","c","d","e","f","g"
Processor,,2 x AMD EPYC 9254 24-Core @ 2.90GHz (48 Cores / 96 Threads),2 x AMD EPYC 9254 24-Core @ 2.90GHz (48 Cores / 96 Threads),2 x AMD EPYC 9254 24-Core @ 2.90GHz (48 Cores / 96 Threads),AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads),AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads),AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads),AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads)
Motherboard,,Supermicro H13DSH (1.5 BIOS),Supermicro H13DSH (1.5 BIOS),Supermicro H13DSH (1.5 BIOS),Supermicro H13SSW (1.1 BIOS),Supermicro H13SSW (1.1 BIOS),Supermicro H13SSW (1.1 BIOS),Supermicro H13SSW (1.1 BIOS)
Memory,,24 x 32 GB DDR5-4800MT/s Samsung M321R4GA3BB6-CQKET,24 x 32 GB DDR5-4800MT/s Samsung M321R4GA3BB6-CQKET,24 x 32 GB DDR5-4800MT/s Samsung M321R4GA3BB6-CQKET,12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N,12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N,12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N,12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N
Disk,,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07,2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07
Graphics,,astdrmfb,astdrmfb,astdrmfb,astdrmfb,astdrmfb,astdrmfb,astdrmfb
OS,,AlmaLinux 9.2,AlmaLinux 9.2,AlmaLinux 9.2,AlmaLinux 9.2,AlmaLinux 9.2,AlmaLinux 9.2,AlmaLinux 9.2
Kernel,,5.14.0-284.25.1.el9_2.x86_64 (x86_64),5.14.0-284.25.1.el9_2.x86_64 (x86_64),5.14.0-284.25.1.el9_2.x86_64 (x86_64),5.14.0-284.25.1.el9_2.x86_64 (x86_64),5.14.0-284.25.1.el9_2.x86_64 (x86_64),5.14.0-284.25.1.el9_2.x86_64 (x86_64),5.14.0-284.25.1.el9_2.x86_64 (x86_64)
Compiler,,GCC 11.3.1 20221121,GCC 11.3.1 20221121,GCC 11.3.1 20221121,GCC 11.3.1 20221121,GCC 11.3.1 20221121,GCC 11.3.1 20221121,GCC 11.3.1 20221121
File-System,,ext4,ext4,ext4,ext4,ext4,ext4,ext4
Screen Resolution,,1024x768,1024x768,1024x768,1024x768,1024x768,1024x768,1024x768
,,"a","b","c","d","e","f","g"
"OpenRadioss - Model: Bumper Beam (sec)",LIB,,,,,,,
"OpenRadioss - Model: Chrysler Neon 1M (sec)",LIB,,,,,,,
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,,,,,,,
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,,,,,,,
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,,,,,,,
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,,,,,,,
"Remhos - Test: Sample Remap Example (sec)",LIB,16.346,16.791,16.243,30.761,30.845,30.725,30.75
"SPECFEM3D - Model: Mount St. Helens (sec)",LIB,11.024765775,11.318495709,11.32735977,26.736414118,26.799143446,26.873168455,27.696631371
"SPECFEM3D - Model: Layered Halfspace (sec)",LIB,26.885983804,28.65210863,27.490850157,71.614294327,70.189028506,70.542255905,69.955609165
"SPECFEM3D - Model: Tomographic Model (sec)",LIB,12.312946652,12.100595947,12.040917877,27.330985588,27.459821308,26.973757395,27.746475162
"SPECFEM3D - Model: Homogeneous Halfspace (sec)",LIB,15.10511773,14.46058698,14.808273365,35.571684908,35.030134889,35.535073001,35.378600021
"SPECFEM3D - Model: Water-layered Halfspace (sec)",LIB,26.985020908,29.460761197,27.060235079,62.441749585,62.325146828,61.281769124,62.810924376
"nekRS - Input: Kershaw (flops/rank)",HIB,11106900000,11240300000,10826700000,10318900000,10264000000,9976450000,10500600000
"nekRS - Input: TurboPipe Periodic (flops/rank)",HIB,6767710000,6757360000,6754170000,7934570000,7931010000,7955790000,7964910000
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,54.9017,55.3925,55.4037,21.4811,21.4357,21.5913,21.5847
"Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,56.0871,56.4551,56.8078,22.585,22.5694,22.6566,22.7745
"Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,60.1449,59.9124,59.7929,24.6872,24.7343,24.7047,24.8193
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,53.5733,53.8135,53.6927,22.2614,22.1577,22.149,22.1901
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,67.3378,67.1951,67.5038,28.3643,28.3141,28.3237,28.4793
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,56.4853,56.6902,56.9327,23.8733,23.9393,23.9354,23.8796
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,5.203,5.149,5.049,4.107,4.114,4.138,4.143
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,90.811,91.322,90.417,66.988,67.721,67.393,67.811
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,163.459,166.378,163.055,163.189,162.608,161.847,160.322
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,163.013,166.692,161.495,161.854,162.051,160.798,161.324
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,12.477,12.591,12.617,10.91,10.984,10.736,11.016
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,141.219,138.338,143.545,118.946,119.307,118.486,118.481
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,422.994,427.686,431.895,526.216,525.173,521.518,528.533
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,510.361,542.611,516.906,604.986,597.011,585.368,586.748
"Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,1.83,1.83,1.83,0.72,0.72,0.72,0.72
"Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,1.84,1.84,1.82,0.72,0.72,0.72,0.72
"Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,0.86,0.86,0.87,0.34,0.34,0.34,0.34
"OSPRay - Benchmark: particle_volume/ao/real_time (Items/sec)",HIB,15.986,15.9785,15.9872,5.57469,5.54107,5.5732,5.57553
"OSPRay - Benchmark: particle_volume/scivis/real_time (Items/sec)",HIB,15.9528,15.9888,15.9778,5.57001,5.56353,5.55581,5.56539
"OSPRay - Benchmark: particle_volume/pathtracer/real_time (Items/sec)",HIB,215.096,214.074,214.136,151.905,151.506,151.78,151.681
"OSPRay - Benchmark: gravity_spheres_volume/dim_512/ao/real_time (Items/sec)",HIB,14.2369,14.1783,14.1399,5.60747,5.6204,5.61454,5.62278
"OSPRay - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time (Items/sec)",HIB,13.8739,13.7666,13.8317,5.45329,5.46153,5.45227,5.47725
"OSPRay - Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time (Items/sec)",HIB,16.3468,16.4365,16.535,6.58745,6.5827,6.59563,6.60085
"Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,27.354,27.241,27.408,55.173,55.093,55.148,55.172
"Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,,,,,,,
"Liquid-DSP - Threads: 1 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,39499000,39486000,39453000,35228000,35315000,35271000,35236000
"Liquid-DSP - Threads: 1 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,59401000,59296000,57519000,52665000,52827000,52879000,52854000
"Liquid-DSP - Threads: 2 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,77181000,77019000,76924000,67054000,68846000,68861000,68678000
"Liquid-DSP - Threads: 2 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,117490000,114010000,118550000,105650000,105480000,105740000,104800000
"Liquid-DSP - Threads: 4 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,153850000,153690000,153670000,138600000,138620000,138580000,138460000
"Liquid-DSP - Threads: 4 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,196220000,196590000,194510000,188930000,191230000,189880000,190750000
"Liquid-DSP - Threads: 8 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,307540000,305110000,306760000,278030000,277780000,276390000,277410000
"Liquid-DSP - Threads: 8 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,369430000,366930000,366990000,363310000,357990000,350450000,357810000
"Liquid-DSP - Threads: 1 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,13909000,14021000,14225000,12683000,12366000,12681000,12256000
"Liquid-DSP - Threads: 16 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,594230000,602470000,603650000,545360000,545140000,545020000,543050000
"Liquid-DSP - Threads: 16 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,699740000,692760000,674930000,689150000,692920000,693340000,682070000
"Liquid-DSP - Threads: 2 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,27901000,27736000,28227000,24627000,25207000,25199000,22727000
"Liquid-DSP - Threads: 32 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,1183500000,1190300000,1184800000,1047100000,1046600000,1041900000,1047100000
"Liquid-DSP - Threads: 32 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,1192100000,1214200000,1254800000,1035000000,1032000000,1024600000,1033400000
"Liquid-DSP - Threads: 4 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,52911000,55588000,55165000,50258000,50380000,49977000,49556000
"Liquid-DSP - Threads: 64 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,2207700000,2212100000,2206800000,1059500000,1057500000,1057100000,1056200000
"Liquid-DSP - Threads: 64 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,1994400000,2001900000,2010300000,1093300000,1095400000,1094600000,1099300000
"Liquid-DSP - Threads: 8 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,109870000,108080000,109140000,99594000,97005000,99441000,100170000
"Liquid-DSP - Threads: 96 - Buffer Length: 256 - Filter Length: 32 (samples/s)",HIB,3005800000,2995400000,2999800000,1065200000,1065100000,1065300000,1065700000
"Liquid-DSP - Threads: 96 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,2559800000,2571100000,2564900000,1120800000,1117800000,1120500000,1118200000
"Liquid-DSP - Threads: 16 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,216080000,216150000,214910000,193850000,196040000,194500000,194670000
"Liquid-DSP - Threads: 32 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,425810000,429620000,424400000,273760000,273480000,273390000,274070000
"Liquid-DSP - Threads: 64 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,622560000,610950000,622630000,282920000,281830000,283030000,281730000
"Liquid-DSP - Threads: 96 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,711640000,718140000,715030000,286250000,285880000,285920000,286530000
"TiDB Community Server - Test: oltp_read_write - Threads: 1 (Queries/sec)",HIB,2540,2510,2485,,3209,3218,3195
"TiDB Community Server - Test: oltp_read_write - Threads: 16 (Queries/sec)",HIB,38331,36950,37368,36480,36784,36125,36088
"TiDB Community Server - Test: oltp_read_write - Threads: 32 (Queries/sec)",HIB,58974,61520,59630,46977,46737,47141,46993
"TiDB Community Server - Test: oltp_read_write - Threads: 64 (Queries/sec)",HIB,79090,80183,78469,55334,53893,54956,55301
"TiDB Community Server - Test: oltp_point_select - Threads: 1 (Queries/sec)",HIB,4331,4405,4471,5898,5976,5954,
"TiDB Community Server - Test: oltp_read_write - Threads: 128 (Queries/sec)",HIB,85757,89099,,59727,60145,60310,59944
"TiDB Community Server - Test: oltp_update_index - Threads: 1 (Queries/sec)",HIB,1212,,1189,1479,1490,1483,1481
"TiDB Community Server - Test: oltp_point_select - Threads: 16 (Queries/sec)",HIB,,67515,65406,,70250,70105,69923
"TiDB Community Server - Test: oltp_point_select - Threads: 32 (Queries/sec)",HIB,104627,106180,,98149,96907,97368,96840
"TiDB Community Server - Test: oltp_point_select - Threads: 64 (Queries/sec)",HIB,127567,130802,,115675,118657,119092,118549
"TiDB Community Server - Test: oltp_update_index - Threads: 16 (Queries/sec)",HIB,12558,,12681,12622,12567,12692,12627
"TiDB Community Server - Test: oltp_update_index - Threads: 32 (Queries/sec)",HIB,18361,17817,17565,17612,17117,,17135
"TiDB Community Server - Test: oltp_update_index - Threads: 64 (Queries/sec)",HIB,,24371,23324,21108,21271,21067,
"TiDB Community Server - Test: oltp_point_select - Threads: 128 (Queries/sec)",HIB,159242,159728,149962,129492,129904,130389,
"TiDB Community Server - Test: oltp_update_index - Threads: 128 (Queries/sec)",HIB,27087,27464,26546,,24611,24830,24574
"TiDB Community Server - Test: oltp_update_non_index - Threads: 1 (Queries/sec)",HIB,1328,1312,1381,1693,1708,1697,1705
"TiDB Community Server - Test: oltp_update_non_index - Threads: 16 (Queries/sec)",HIB,18095,18068,,18563,18557,,18735
"TiDB Community Server - Test: oltp_update_non_index - Threads: 32 (Queries/sec)",HIB,28735,28914,,26273,26285,26695,
"TiDB Community Server - Test: oltp_update_non_index - Threads: 64 (Queries/sec)",HIB,41281,39759,39106,34224,33881,34470,34107
"TiDB Community Server - Test: oltp_update_non_index - Threads: 128 (Queries/sec)",HIB,51105,,52865,,42138,41424,41695
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,39.4951,39.4681,39.4464,13.0694,12.9433,13.0853,13.073
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,605.0388,605.7307,605.9183,606.101,607.913,607.8171,607.1628
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1417.0706,1403.065,1418.9041,508.087,511.4098,508.2088,509.139
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,16.9074,17.0669,16.8863,15.7246,15.6245,15.721,15.6892
"Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,672.4635,672.3734,671.2554,257.2728,257.894,257.5046,257.2808
"Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,35.628,35.6422,35.6825,31.0525,30.9867,31.0292,31.0574
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,201.3925,201.2528,201.5402,71.137,71.2727,71.044,70.9275
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,118.7509,118.9482,118.7801,112.2499,112.0574,112.413,112.4779
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,485.6725,488.1264,489.1106,162.8502,163.1361,162.9294,162.9937
"Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,49.3653,49.1082,49.0173,49.0863,49.0094,49.0712,49.0259
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,5137.0114,5138.8341,5153.6644,1599.2079,1599.1543,1600.5275,1602.5221
"Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,4.6508,4.6476,4.6348,4.996,4.9859,4.9877,4.9787
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,215.6383,215.9254,215.647,71.9189,71.9146,71.9401,71.9003
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,111.0131,110.9152,111.025,111.1081,111.0888,110.8852,110.9759
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,49.3258,49.1666,47.1535,16.1648,16.1392,16.1307,16.0672
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,485.7175,487.3599,507.4786,493.596,494.2575,494.2211,495.6033
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,489.1203,489.4464,487.0522,163.5559,162.9298,162.8976,163.2282
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,49.0092,48.9703,49.2055,48.8729,49.0598,49.0714,48.9837
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,218.1464,219.5263,218.5162,72.455,72.6571,72.5736,72.6879
"Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,109.8027,109.2332,109.5847,110.1114,109.9654,110.0001,109.9037
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,322.2505,321.1829,321.5082,108.909,109.0938,109.09,109.2191
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,74.3211,74.5553,74.5031,73.3058,73.2609,73.2163,73.1867
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,68.5988,68.6617,68.6287,24.4833,24.4725,24.5238,24.4607
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,347.6612,347.2189,347.3728,325.8763,325.7416,324.9568,325.5075
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,718.9189,717.9693,716.1404,240.5529,240.2349,240.1642,239.5176
"Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,33.3412,33.3798,33.4637,33.2242,33.2625,33.2751,33.3674
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,158.924,159.0596,164.6131,55.6132,55.4634,55.5428,55.4264
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,150.5897,150.6055,145.2562,143.7643,144.1013,143.6922,144.1053
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,39.4391,39.4539,39.4183,13.1312,13.1187,13.0934,13.0596
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,605.758,606.6693,605.8765,606.5773,606.755,606.7852,608.7163
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,26.2,26.24,26.12,72,71.44,71.96,72.01
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,66.42,66.64,66.72,182.99,182.56,181.7,183.29
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,33.22,33.17,33.03,90.03,90.31,90.26,90.63
"Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,254.88,255.3,254.72,670.87,670.64,667.87,669.09
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,80.54,80.76,80.41,224.15,224.1,223.95,224.12
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,30.41,30.44,30.43,10.47,10.47,10.48,10.48
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,393.6,393.23,393.37,761.59,761.16,760.57,759.92
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,282.55,284.22,282.67,107.02,107.27,107.39,107.04
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,42.44,42.2,42.43,74.71,74.5,74.43,74.71
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,283.97,284.99,284.31,106.9,107.24,106.76,107.24
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,42.24,42.09,42.19,74.81,74.54,74.87,74.58
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,2033.17,2028.01,2029.79,797.64,793.75,791.74,793.9
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,5.89,5.91,5.9,10.01,10.06,10.09,10.06
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,56.01,56.06,56.02,20.03,20,20.01,20.05
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,213.94,213.62,213.79,398.52,398.91,399.24,398.13
"OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,5882.91,5836.27,5840.53,2564.78,2562.54,2539.97,2557.66
"OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,2.03,2.05,2.05,3.11,3.11,3.14,3.12
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,748.44,750.49,757.38,344.67,342.81,343.49,341.36
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,16.02,15.98,15.83,23.2,23.32,23.28,23.42
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,2873.24,2880.58,2881.14,1175.67,1174.6,1180.85,1175.58
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,4.17,4.16,4.16,6.79,6.8,6.76,6.79
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,2945.26,2986.46,2987.33,1039.61,1039.82,1038.47,1039.37
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,16.26,16.02,16.02,15.36,15.36,15.38,15.37
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,9837.58,9849.07,9845.27,3540.88,3544.18,3548.78,3533.64
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,4.86,4.85,4.86,4.51,4.51,4.5,4.52
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,842.91,854.51,849.3,370.57,373.64,369.26,372.26
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,14.23,14.03,14.12,21.57,21.4,21.65,21.47
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,317.22,317.28,317.33,124.12,123.61,124.3,123.41
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,37.8,37.79,37.79,64.41,64.68,64.31,64.77
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,5776.94,5780.44,5802.65,2013.77,2007.53,2004.76,2006.09
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,8.28,8.27,8.24,7.93,7.96,7.97,7.96
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,2454.09,2450.26,2455.51,1036.99,1028.64,1041.87,1031.6
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,4.88,4.89,4.88,7.7,7.77,7.67,7.74
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,1560.03,1546.02,1551.63,532.59,530.99,533.74,538.01
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,30.72,31,30.89,30.02,30.1,29.95,29.72
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,86884.64,87359.23,86789.8,32002.62,32032.06,31951.64,32008.03
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.54,0.54,0.54,0.49,0.49,0.49,0.49
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,1244.69,1239.67,1237.29,395.66,432.32,431.94,432.2
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,38.5,38.66,38.75,40.4,36.98,37.01,36.98
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,120606.38,120728.22,123484.28,44958.07,44933.27,44968.43,45097.99
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.34,0.34,0.34,0.35,0.35,0.35,0.35
"Apache Cassandra - Test: Writes (Op/s)",HIB,248095,256661,270480,197866,195798,196287,197092
"Apache Hadoop - Operation: Open - Threads: 50 - Files: 100000 (Ops per sec)",HIB,460829,469484,401606,578035,552486,578035,546448
"Apache Hadoop - Operation: Open - Threads: 100 - Files: 100000 (Ops per sec)",HIB,420168,404858,403226,529101,294985,523560,460829
"Apache Hadoop - Operation: Open - Threads: 50 - Files: 1000000 (Ops per sec)",HIB,1126126,1020408,683995,278319,251004,1221001,654022
"Apache Hadoop - Operation: Create - Threads: 50 - Files: 100000 (Ops per sec)",HIB,43649,41288,43937,58617,58617,58343,60680
"Apache Hadoop - Operation: Delete - Threads: 50 - Files: 100000 (Ops per sec)",HIB,91075,73801,90580,101010,100604,96993,103950
"Apache Hadoop - Operation: Open - Threads: 100 - Files: 1000000 (Ops per sec)",HIB,215332,173822,185874,1248439,1204819,1303781,1107420
"Apache Hadoop - Operation: Rename - Threads: 50 - Files: 100000 (Ops per sec)",HIB,70522,73046,77101,82372,82237,81633,82237
"Apache Hadoop - Operation: Create - Threads: 100 - Files: 100000 (Ops per sec)",HIB,40733,37425,35075,57971,58824,59382,58928
"Apache Hadoop - Operation: Create - Threads: 50 - Files: 1000000 (Ops per sec)",HIB,53665,52119,52260,72134,70897,69920,72706
"Apache Hadoop - Operation: Delete - Threads: 100 - Files: 100000 (Ops per sec)",HIB,87566,90827,73475,105708,98039,99404,102564
"Apache Hadoop - Operation: Delete - Threads: 50 - Files: 1000000 (Ops per sec)",HIB,98932,97314,90147,111012,113327,111198,110828
"Apache Hadoop - Operation: Rename - Threads: 100 - Files: 100000 (Ops per sec)",HIB,75529,69348,67159,82102,83822,79491,80386
"Apache Hadoop - Operation: Rename - Threads: 50 - Files: 1000000 (Ops per sec)",HIB,73239,71679,74638,83921,84041,82501,84810
"Apache Hadoop - Operation: Create - Threads: 100 - Files: 1000000 (Ops per sec)",HIB,46145,44437,44001,71296,70057,70537,70922
"Apache Hadoop - Operation: Delete - Threads: 100 - Files: 1000000 (Ops per sec)",HIB,90114,86715,97031,112613,113225,110803,113895
"Apache Hadoop - Operation: Rename - Threads: 100 - Files: 1000000 (Ops per sec)",HIB,73078,72129,66827,81208,84360,85815,85763
"Apache Hadoop - Operation: File Status - Threads: 50 - Files: 100000 (Ops per sec)",HIB,529101,862069,657895,632911,389105,709220,561798
"Apache Hadoop - Operation: File Status - Threads: 100 - Files: 100000 (Ops per sec)",HIB,515464,458716,729927,591716,613497,478469,487805
"Apache Hadoop - Operation: File Status - Threads: 50 - Files: 1000000 (Ops per sec)",HIB,2173913,1941748,284252,1818182,320924,1795332,2036660
"Apache Hadoop - Operation: File Status - Threads: 100 - Files: 1000000 (Ops per sec)",HIB,1886792,161970,1893939,600601,235627,1964637,2049180
"Kripke - (Throughput FoM)",HIB,,,,240994500,236243900,236591000,237175700
"BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,772162,768517,762529,298064,296125,295603,295522
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 (sec)",LIB,,,,1.657,1.654,1.657,1.648
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 (sec)",LIB,,,,38.105,38.067,38.015,37.95
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 (sec)",LIB,,,,98.98,99.415,97.987,97.529
"Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,,,,24.845,24.8282,24.887,24.9619
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,,,,22.3517,22.2911,22.2676,22.2559
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,,,,21.8943,21.9909,21.7746,21.8305
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,,,,27.7438,27.8293,27.826,27.91
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,,,,23.3531,23.5283,23.5042,23.7091
"Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,,,,22.3922,22.3422,22.4407,22.4215
"OpenVKL - Benchmark: vklBenchmarkCPU Scalar (Items / Sec)",HIB,,,,191,190,191,191
"OpenVKL - Benchmark: vklBenchmarkCPU ISPC (Items / Sec)",HIB,,,,487,487,488,489
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,,,,2.13332,2.1257,2.13062,2.11813
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,1.55824,1.54911,1.57282,1.55118
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,1.33789,1.33861,1.34183,1.33564
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,,,,3.81576,3.84421,3.81823,3.82381
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,0.628236,0.633975,0.630325,0.629108
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,3.05991,3.0637,3.05674,3.05458
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,,,,3.37782,3.38436,3.37956,3.38156
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,0.847805,0.844434,0.850691,0.843492
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,1.91374,1.91781,1.91422,1.91274
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,,,,2.49408,2.56522,2.49714,2.51441
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,0.652259,0.65761,0.653182,0.6477
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,1.03749,1.14432,1.00136,1.12723
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,,,,1.25758,1.28043,1.20653,1.27918
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,0.60395,0.575794,0.600834,0.61232
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,1.02875,1.05425,1.06144,1.04567
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,,,,1641.92,1641,1636.76,1637.37
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,1642.51,1639.36,1636.44,1631.99
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,1643.99,1643.97,1642.35,1641.4
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,,,,838.516,849.712,851.494,848.032
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,849.163,851.659,849.344,837.595
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,847.38,841.078,845.308,847.417
"Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,,,,0.72,0.72,0.72,0.72
"Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,,,,0.72,0.72,0.72,0.72
"Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,,,,0.34,0.34,0.34,0.34