tests for a future article.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2305086-NE-7773X808085
7773x
tests for a future article.
,,"a","b","5 a","5 b","5 2p a","5 2p b","7373x","2 x AMD EPYC 7373X 16-Core","7373X 2P"
Processor,,AMD EPYC 7773X 64-Core @ 2.20GHz (64 Cores / 128 Threads),AMD EPYC 7773X 64-Core @ 2.20GHz (64 Cores / 128 Threads),AMD EPYC 7573X 32-Core @ 2.80GHz (32 Cores / 64 Threads),AMD EPYC 7573X 32-Core @ 2.80GHz (32 Cores / 64 Threads),2 x AMD EPYC 7573X 32-Core @ 2.80GHz (64 Cores / 128 Threads),2 x AMD EPYC 7573X 32-Core @ 2.80GHz (64 Cores / 128 Threads),AMD EPYC 7373X 16-Core @ 3.05GHz (16 Cores / 32 Threads),2 x AMD EPYC 7373X 16-Core @ 3.05GHz (32 Cores / 64 Threads),2 x AMD EPYC 7373X 16-Core @ 3.05GHz (32 Cores / 64 Threads)
Motherboard,,AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS)
Chipset,,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse
Memory,,256GB,256GB,256GB,256GB,512GB,512GB,256GB,512GB,512GB
Disk,,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP
Graphics,,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED
Monitor,,VE228,VE228,VE228,VE228,VE228,VE228,VE228,VE228,VE228
Network,,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710
OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04
Kernel,,5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64)
Desktop,,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4
Display Server,,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3
Vulkan,,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204
Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0
File-System,,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080
,,"a","b","5 a","5 b","5 2p a","5 2p b","7373x","2 x AMD EPYC 7373X 16-Core","7373X 2P"
"SPECFEM3D - Model: Tomographic Model (sec)",LIB,13.862202300,13.530179394,19.089664857,19.630096342,11.224767813,11.797525585,35.505846619,18.033266557,18.331770412
"SPECFEM3D - Model: Homogeneous Halfspace (sec)",LIB,17.209349082,16.817080246,24.987445867,25.089622797,14.491419469,14.415931158,51.264616343,23.273738774,23.898547572
"SPECFEM3D - Model: Mount St. Helens (sec)",LIB,11.678414616,11.75332146,18.86219907,19.355553092,9.609453868,9.59476935,37.795953129,18.406629769,17.820390395
"SPECFEM3D - Model: Layered Halfspace (sec)",LIB,30.518912661,30.115899704,49.136149469,48.738676454,25.221006745,25.472190291,91.272692415,48.717394203,49.831882811
"Google Draco - Model: Lion (ms)",LIB,4867,4885,4760,,4734,4818,4563,4642,4614
"Google Draco - Model: Church Facade (ms)",LIB,5793,5833,5718,,5682,5729,5406,5498,5485
"eSpeak-NG Speech Engine - Text-To-Speech Synthesis (sec)",LIB,,28.157,27.826,,27.868,28.137,26.507,26.467,26.514
"SPECFEM3D - Model: Water-layered Halfspace (sec)",LIB,28.081540950,27.467540273,45.70942713,44.334574335,23.936065997,23.268032641,78.600264543,43.780135473,43.859744419
"Z3 Theorem Prover - SMT File: 2.smt2 (sec)",LIB,,,,,,,,70.286,70.51
"QuantLib - (MFLOPS)",HIB,2746.5,2692.4,2756.9,2820.4,2760.9,2850.8,2854.1,2894.2,2907.3
"LeelaChessZero - Backend: BLAS (Nodes/s)",HIB,,5554,1419,,8284,7991,1955,1676,1709
"LeelaChessZero - Backend: Eigen (Nodes/s)",HIB,,5142,1238,,8286,7816,1714,1450,1357
"CloverLeaf - Lagrangian-Eulerian Hydrodynamics (sec)",LIB,,11.34,12.09,,15.67,15.51,18.26,30.67,28.59
"OpenCV - Test: Core (ms)",LIB,,77061,68343,,,236445,,85621,98738
"OpenCV - Test: Graph API (ms)",LIB,,235810,206970,,,419702,,263067,363745
"OpenCV - Test: Stitching (ms)",LIB,,201160,184032,,,287492,,232977,228123
"OpenCV - Test: Object Detection (ms)",LIB,,31910,27739,,,88553,,31850,32187
"OpenCV - Test: DNN - Deep Neural Network (ms)",LIB,,39756,39997,,,87133,,65657,82360
"NCNN - Target: CPU - Model: mobilenet (ms)",LIB,,17.84,13.7,,77.77,115.68,12.23,67.15,79.82
"NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,,11.3,6.46,,27.7,38.67,4.92,28.85,33.16
"NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,,10.29,6.19,,21.26,28.88,4.5,24.19,29.52
"NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,,15.6,7.73,,33.27,37.89,5.86,31.88,31.65
"NCNN - Target: CPU - Model: mnasnet (ms)",LIB,,11.71,6.08,,38.49,49.46,4.52,37.62,38.98
"NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,,15.44,9.03,,35.12,60.79,6.97,46.67,46.69
"NCNN - Target: CPU - Model: blazeface (ms)",LIB,,8.12,3.82,,14.65,24.56,2.4,18.4,18.75
"NCNN - Target: CPU - Model: googlenet (ms)",LIB,,19.09,14.11,,93.29,112.43,11.76,27.63,45.41
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,,24.04,21.08,,33.55,32.81,20.47,32.77,29.82
"NCNN - Target: CPU - Model: resnet18 (ms)",LIB,,10.89,8.12,,38.94,51.8,7.05,13.62,15.14
"NCNN - Target: CPU - Model: alexnet (ms)",LIB,,7.13,5.48,,18.6,28.55,4.76,9.78,10.29
"NCNN - Target: CPU - Model: resnet50 (ms)",LIB,,19.58,14.8,,80.81,120.27,13.25,25.38,30.71
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,,23.92,19.98,,38.1,45.89,18.23,31.98,33.74
"NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,,19.32,14.85,,37.17,35.81,12.71,22.58,23.89
"NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,,53.52,26.34,,100.65,128.35,17.6,86.22,84.88
"NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,,133.39,126.26,,144.31,145.49,140.06,145.33,144.55
"NCNN - Target: CPU - Model: FastestDet (ms)",LIB,,19.08,9.25,,40.45,53.25,7.35,21.36,39.48
"GROMACS - Implementation: MPI CPU - Input: water_GMX50_bare (Ns/Day)",HIB,7.290,7.299,5.022,,8.285,8.222,2.985,5.248,5.193
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,,1.26107,1.37996,,2.67801,2.88451,1.87446,2.05818,2.17496
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,,1.24618,0.62593,,0.911806,0.917226,0.609746,0.750853,0.948143
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,,0.827622,1.14656,,0.674336,0.669349,1.93416,1.03456,1.04348
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,,6.92145,4.49565,,10.5221,10.3685,6.82625,5.78798,5.87951
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,,3.12487,2.76234,,1.85167,1.89859,3.77803,2.70057,2.73357
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,,1183.63,1182.61,,1390.36,1385.33,1760.49,1377.39,1370.61
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,,749.622,679.645,,1212.84,1305.96,906.609,1177.81,1349.92
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,,12.16,8.23,,15.86,15.76,4.74,8.86,
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,,2608.34,1935.6,,2013.52,2020.21,1684.86,1782.06,
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,,8.05,5.48,,10.54,10.63,3.17,6.17,
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,,3911.97,2881.04,,2975.15,2948.39,2493.98,2547.35,
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,,8.04,5.47,,10.64,10.64,3.16,6.1,
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,,3927,2886.12,,2946.97,2952.76,2496.52,2595.65,
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,,1205.11,841.49,,1632.81,1623.83,400.07,786.17,
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,,26.54,19,,19.58,19.69,19.99,20.33,
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,,27.03,17.92,,34.83,34.91,9.71,19.31,
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,,1175.01,886.41,,914.24,912.42,821.36,826.77,
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,,1889.05,1244.86,,2504.36,2498.74,652.03,1274.04,
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,,16.93,12.84,,12.76,12.79,12.26,12.54,
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,,1198.45,822.19,,1594.14,1592.71,454.9,892.67,
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,,26.68,19.45,,20.06,20.07,17.58,17.91,
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,,138.84,92.61,,175.48,176.76,52.66,98.39,
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,,230.27,172.53,,182.1,180.91,151.73,162.5,
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,,2674.29,1767.13,,3501.69,3504.15,964.19,1914.22,
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,,23.92,18.1,,18.26,18.25,16.58,16.7,
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,,1888.2,1252.05,,2523.57,2524.05,598.4,1181.75,
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,,16.93,12.77,,12.66,12.66,13.36,13.52,
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,,35737.82,25209.62,,39455.86,38800.34,14994.76,29028.25,
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,,1.74,1.26,,1.37,1.4,1.06,1.09,
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,,38091.46,27340.96,,,40352.48,16278.25,31155.59,
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,,1.62,1.16,,,1.33,0.97,1.01,
"ASKAP - Test: tConvolve MT - Gridding (Million Grid Points/sec)",HIB,,5493.35,6599.68,,7738.59,7176.41,8783.7,9627.34,9605.63
"ASKAP - Test: tConvolve MT - Degridding (Million Grid Points/sec)",HIB,,8308.33,9611.05,,12506.7,11068.8,10352.6,11891.4,12025.7
"ASKAP - Test: tConvolve MPI - Degridding (Mpix/sec)",HIB,,32799.5,20991.7,,41983.3,41983.3,11662,21866.3,21420.1
"ASKAP - Test: tConvolve MPI - Gridding (Mpix/sec)",HIB,,36827.5,24990.1,,49980.1,51199.1,15435,29155.1,29155.1
"ASKAP - Test: tConvolve OpenMP - Gridding (Million Grid Points/sec)",HIB,,20481.2,17750.4,,12102.5,12678.9,13312.8,11576.3,12102.5
"ASKAP - Test: tConvolve OpenMP - Degridding (Million Grid Points/sec)",HIB,,19018.3,19018.3,,16641,15662.1,14792,13312.8,13312.8
"ASKAP - Test: Hogbom Clean OpenMP (Iterations/sec)",HIB,,806.452,869.565,,436.681,434.783,729.927,458.716,458.716
"ACES DGEMM - Sustained Floating-Point Rate (GFLOP/s)",HIB,29.383496,29.04569,17.8745,18.6403,31.344515,31.760876,8.024336,14.481647,14.704153
"Pennant - Test: sedovbig (Hydro Cycle Time - sec)",LIB,,9.56361,14.00111,,7.656369,7.793325,23.87947,13.28648,13.31026
"Pennant - Test: leblancbig (Hydro Cycle Time - sec)",LIB,,5.104078,7.974022,,4.294731,4.418012,14.50909,7.465373,7.419739
"LULESH - (z/s)",HIB,,22257.137,20920.487,,42030.038,42551.898,10188.248,27032.903,27107.143
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,24.729957,25.596085,22.337396,22.706399,22.563946,23.335275,26.386727,24.265467,24.672394
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,40.450568,40.244428,50.745904,50.699752,33.001079,32.974316,78.749334,76.087652,74.593848
"OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Mesh Time (sec)",LIB,25.348583,120.39337,117.4378,117.6045,99.384145,99.93268,149.00372,114.44612,116.27444
"OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Execution Time (sec)",LIB,40.481652,363.7359,428.6592,427.71276,205.46392,203.65118,596.96916,334.89524,332.03432
"Xcompact3d Incompact3d - Input: input.i3d 129 Cells Per Direction (sec)",LIB,,4.43804121,5.06756401,,2.48654294,2.48386908,6.86468983,3.9324739,4.75395298
"Xcompact3d Incompact3d - Input: input.i3d 193 Cells Per Direction (sec)",LIB,,17.2118473,19.6305008,,10.6241302,10.7624416,25.2174606,13.799696,13.717701
"Timed FFmpeg Compilation - Time To Compile (sec)",LIB,16.928,17.042,20.378,20.64,15.455,15.344,29.979,19.56,19.697
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,,396928,271918,,403739,396844,155879,241803,243862
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,,411213,244220,,453996,440740,128235,232623,236136
"John The Ripper - Test: bcrypt (Real C/S)",HIB,86230,91276,60192,60152,118502,117542,31573,62360,62551
"John The Ripper - Test: WPA PSK (Real C/S)",HIB,201388,202957,130848,131072,259413,258457,70803,136260,139127
"John The Ripper - Test: Blowfish (Real C/S)",HIB,86460,87360,60325,60345,118579,117771,31651,62244,62302
"John The Ripper - Test: HMAC-SHA512 (Real C/S)",HIB,136796000,135165000,96059000,94924000,79002000,73260000,59680000,67213000,68530000
"John The Ripper - Test: MD5 (Real C/S)",HIB,5534000,5543000,3621000,3605000,6845000,6683000,1959000,3735000,3739000
"Timed LLVM Compilation - Build System: Ninja (sec)",LIB,165.707,164.449,230.378,231.091,138.717,138.565,391.792,211.489,212.52
"Timed LLVM Compilation - Build System: Unix Makefiles (sec)",LIB,246.957,248.481,290.539,297.223,219.403,221.789,433.971,277.061,271.829
"Zstd Compression - Compression Level: 3 - Compression Speed (MB/s)",HIB,,2819,2856.6,,2783.7,2775.9,2661,2842.3,2801.4
"Zstd Compression - Compression Level: 3 - Decompression Speed (MB/s)",HIB,,1277.3,1326.5,,1306.7,1309.5,1281.1,1384.1,1362.4
"Zstd Compression - Compression Level: 8 - Compression Speed (MB/s)",HIB,,988.5,1067.8,,1024,1013.4,913.5,1022.3,992.4
"Zstd Compression - Compression Level: 8 - Decompression Speed (MB/s)",HIB,,1390,1438.8,,1437.5,1441.1,1523.9,1523.6,1518.1
"Zstd Compression - Compression Level: 12 - Compression Speed (MB/s)",HIB,,270.8,289.1,,283.6,282.8,305.1,288.9,295
"Zstd Compression - Compression Level: 12 - Decompression Speed (MB/s)",HIB,,1445.9,1478.1,,1482.7,1498.9,1557.2,1563,1552
"Zstd Compression - Compression Level: 19 - Compression Speed (MB/s)",HIB,,17.6,18.2,,18,18,19.2,18.6,18.9
"Zstd Compression - Compression Level: 19 - Decompression Speed (MB/s)",HIB,,1276.8,1304.2,,1315.6,1312,1389.6,1375.8,1394.3
"Zstd Compression - Compression Level: 3, Long Mode - Compression Speed (MB/s)",HIB,,752.6,854.2,,808.5,741.5,865.4,854.9,813.6
"Zstd Compression - Compression Level: 3, Long Mode - Decompression Speed (MB/s)",HIB,,1300.8,1361.5,,1332.3,1336.5,1413,1415.4,1414.1
"Zstd Compression - Compression Level: 8, Long Mode - Compression Speed (MB/s)",HIB,,744.5,792.1,,702.8,702.2,727,680.9,671.6
"Zstd Compression - Compression Level: 8, Long Mode - Decompression Speed (MB/s)",HIB,,1434.2,1460.1,,1454.7,1445.1,1541.7,1559.8,1538.4
"Zstd Compression - Compression Level: 19, Long Mode - Compression Speed (MB/s)",HIB,,9.3,9.54,,9.57,9.5,10.1,10.1,10.1
"Zstd Compression - Compression Level: 19, Long Mode - Decompression Speed (MB/s)",HIB,,1190.8,1229.1,,1222.9,1227.1,1312.9,1289.9,1292.1
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,4.863,4.826,4.743,4.76,4.784,4.842,3.993,4.644,4.676
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,73.442,67.548,65.337,70.856,62.836,69.536,49.204,58.355,58.697
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,222.837,214.933,220.813,226.733,169.112,176.107,152.194,163.328,162.784
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,195.924,198.135,199.69,196.063,169.658,172.573,147.354,166.539,159.261
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,10.295,10.234,10.76,10.828,10.41,10.495,10.023,10.195,10.434
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,109.984,109.711,107.382,108.364,107.1,104.169,92.984,100.587,101.821
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,604.842,601.984,629.3,622.732,540.729,565.057,487.076,525.637,522.16
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,552.241,549.834,571.084,560.565,525.154,546.034,506.517,510.787,490.986
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,27.61,27.6,42.52,,22.59,22.51,78.75,40.61,40.47
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,72.45,72.02,113.31,,58.55,58.57,212.97,108.3,108.06
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,34.77,34.61,52.68,,27.96,27.9,95.96,49.27,49.44
"Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,260.83,259.87,408.79,,213.6,213.46,768.94,393.87,396.8
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,88.76,88.73,136.58,,71.64,71.73,252.02,127.96,127.5
"FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,47.74,47.206774889,45.71,45.79,54.58,47.07,44.06,45.467307319,50.590873871
"FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,105.78,106.98,110.49,110.29,92.52,107.29,114.63,111.07,99.82
"FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,116.93,116.80915814,110.01,110.14,112.819760537,114.261775562,110.605502327,113.672822126,112.961052185
"PETSc - Test: Streams (MB/s)",HIB,,56185.7504,31992.6068,,,74130.1789,,,
"FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,21.59,21.62,22.95,22.93,22.38,22.10,22.83,22.21,22.35
"FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,173.23,172.56956694,162.19,,170.942711463,173.56002958,162.296027345,169.985789453,165.700132761
"FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,43.73,43.90,46.70,,44.31,43.64,46.67,44.56,45.72
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,173.47,172.533939506,161.54,,168.456941186,173.052257283,162.33,165.871463966,170.679636105
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,43.67,43.90,46.89,,44.97,43.77,46.66,45.67,44.38
"VVenC - Video Input: Bosphorus 4K - Video Preset: Fast (FPS)",HIB,6.286,6.128,6.406,6.39,5.548,5.768,5.719,5.877,5.774
"VVenC - Video Input: Bosphorus 4K - Video Preset: Faster (FPS)",HIB,11.367,11.364,11.961,12.02,9.574,9.906,11.224,10.127,10.083
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Fast (FPS)",HIB,16.552,16.374,16.846,17.253,14.812,15.044,15.801,14.787,14.936
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Faster (FPS)",HIB,30.006,30.114,31.837,31.795,24.492,24.268,31.274,24.314,24.216
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,69.1077,,43.9492,43.9787,81.4508,81.0913,23.589,44.8797,44.216
"Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,63.3711,63.3647,40.2408,40.1199,73.3301,73.2602,21.3851,40.3604,39.9992
"Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,78.4751,,48.5228,48.5074,76.8067,76.6287,24.9073,42.8312,42.74
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,70.5238,,43.9589,44.1884,68.6922,68.7022,23.3587,38.7779,38.4256
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,73.8446,73.828,44.9118,45.1054,73.9612,73.7779,23.5684,40.5062,40.1812
"Z3 Theorem Prover - SMT File: 1.smt2 (sec)",LIB,,,,,,,,21.218,21.717
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,64.5117,64.6409,39.1941,39.2236,64.4091,64.0441,20.1045,35.2408,34.8566
"OpenVKL - Benchmark: vklBenchmark ISPC (Items / Sec)",HIB,470,469,340,339,452,452,213,309,306
"ClickHouse - 100M Rows Hits Dataset, First Run / Cold Cache (Queries/min, Geo Mean)",HIB,,428.51,437.20,,445.18,440.56,351.01,420.29,420.94
"ClickHouse - 100M Rows Hits Dataset, Second Run (Queries/min, Geo Mean)",HIB,,439.07,457.81,,463.68,467.46,386.60,438.36,433.56
"ClickHouse - 100M Rows Hits Dataset, Third Run (Queries/min, Geo Mean)",HIB,,437.35,456.30,,461.53,448.03,384.96,429.56,436.29