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"
"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: mobilenet (ms)",LIB,,17.84,13.7,,77.77,115.68,12.23,67.15,79.82
"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: efficientnet-b0 (ms)",LIB,,15.44,9.03,,35.12,60.79,6.97,46.67,46.69
"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 - Model: resnet18 (ms)",LIB,,10.89,8.12,,38.94,51.8,7.05,13.62,15.14
"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: FastestDet (ms)",LIB,,19.08,9.25,,40.45,53.25,7.35,21.36,39.48
"LeelaChessZero - Backend: Eigen (Nodes/s)",HIB,,5142,1238,,8286,7816,1714,1450,1357
"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: alexnet (ms)",LIB,,7.13,5.48,,18.6,28.55,4.76,9.78,10.29
"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
"LeelaChessZero - Backend: BLAS (Nodes/s)",HIB,,5554,1419,,8284,7991,1955,1676,1709
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,,1888.2,1252.05,,2523.57,2524.05,598.4,1181.75,
"LULESH - (z/s)",HIB,,22257.137,20920.487,,42030.038,42551.898,10188.248,27032.903,27107.143
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,,1205.11,841.49,,1632.81,1623.83,400.07,786.17,
"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
"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
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,,1889.05,1244.86,,2504.36,2498.74,652.03,1274.04,
"John The Ripper - Test: bcrypt (Real C/S)",HIB,86230,91276,60192,60152,118502,117542,31573,62360,62551
"John The Ripper - Test: Blowfish (Real C/S)",HIB,86460,87360,60325,60345,118579,117771,31651,62244,62302
"John The Ripper - Test: WPA PSK (Real C/S)",HIB,201388,202957,130848,131072,259413,258457,70803,136260,139127
"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
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,,2674.29,1767.13,,3501.69,3504.15,964.19,1914.22,
"SPECFEM3D - Model: Layered Halfspace (sec)",LIB,30.518912661,30.115899704,49.136149469,48.738676454,25.221006745,25.472190291,91.272692415,48.717394203,49.831882811
"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
"ASKAP - Test: tConvolve MPI - Degridding (Mpix/sec)",HIB,,32799.5,20991.7,,41983.3,41983.3,11662,21866.3,21420.1
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,,27.03,17.92,,34.83,34.91,9.71,19.31,
"SPECFEM3D - Model: Homogeneous Halfspace (sec)",LIB,17.209349082,16.817080246,24.987445867,25.089622797,14.491419469,14.415931158,51.264616343,23.273738774,23.898547572
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,,411213,244220,,453996,440740,128235,232623,236136
"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
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,,1198.45,822.19,,1594.14,1592.71,454.9,892.67,
"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
"John The Ripper - Test: MD5 (Real C/S)",HIB,5534000,5543000,3621000,3605000,6845000,6683000,1959000,3735000,3739000
"OpenCV - Test: Core (ms)",LIB,,77061,68343,,,236445,,85621,98738
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,69.1077,,43.9492,43.9787,81.4508,81.0913,23.589,44.8797,44.216
"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
"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
"Pennant - Test: leblancbig (Hydro Cycle Time - sec)",LIB,,5.104078,7.974022,,4.294731,4.418012,14.50909,7.465373,7.419739
"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
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,,8.04,5.47,,10.64,10.64,3.16,6.1,
"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: Person Detection FP16 - Device: CPU (FPS)",HIB,,8.05,5.48,,10.54,10.63,3.17,6.17,
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,,12.16,8.23,,15.86,15.76,4.74,8.86,
"ASKAP - Test: tConvolve MPI - Gridding (Mpix/sec)",HIB,,36827.5,24990.1,,49980.1,51199.1,15435,29155.1,29155.1
"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
"OpenCV - Test: Object Detection (ms)",LIB,,31910,27739,,,88553,,31850,32187
"SPECFEM3D - Model: Tomographic Model (sec)",LIB,13.862202300,13.530179394,19.089664857,19.630096342,11.224767813,11.797525585,35.505846619,18.033266557,18.331770412
"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 ISPC - Model: Asian Dragon (FPS)",HIB,73.8446,73.828,44.9118,45.1054,73.9612,73.7779,23.5684,40.5062,40.1812
"Pennant - Test: sedovbig (Hydro Cycle Time - sec)",LIB,,9.56361,14.00111,,7.656369,7.793325,23.87947,13.28648,13.31026
"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
"NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,,19.32,14.85,,37.17,35.81,12.71,22.58,23.89
"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
"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
"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
"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
"CloverLeaf - Lagrangian-Eulerian Hydrodynamics (sec)",LIB,,11.34,12.09,,15.67,15.51,18.26,30.67,28.59
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,,35737.82,25209.62,,39455.86,38800.34,14994.76,29028.25,
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,,396928,271918,,403739,396844,155879,241803,243862
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,,23.92,19.98,,38.1,45.89,18.23,31.98,33.74
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,,38091.46,27340.96,,,40352.48,16278.25,31155.59,
"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
"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
"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
"PETSc - Test: Streams (MB/s)",HIB,,56185.7504,31992.6068,,,74130.1789,,,
"John The Ripper - Test: HMAC-SHA512 (Real C/S)",HIB,136796000,135165000,96059000,94924000,79002000,73260000,59680000,67213000,68530000
"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
"OpenVKL - Benchmark: vklBenchmark ISPC (Items / Sec)",HIB,470,469,340,339,452,452,213,309,306
"OpenCV - Test: DNN - Deep Neural Network (ms)",LIB,,39756,39997,,,87133,,65657,82360
"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: 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
"OpenCV - Test: Graph API (ms)",LIB,,235810,206970,,,419702,,263067,363745
"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
"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: blazeface (ms)",LIB,,8.12,3.82,,14.65,24.56,2.4,18.4,18.75
"ASKAP - Test: Hogbom Clean OpenMP (Iterations/sec)",HIB,,806.452,869.565,,436.681,434.783,729.927,458.716,458.716
"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
"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
"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
"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 MT - Gridding (Million Grid Points/sec)",HIB,,5493.35,6599.68,,7738.59,7176.41,8783.7,9627.34,9605.63
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,,1.62,1.16,,,1.33,0.97,1.01,
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,,1.74,1.26,,1.37,1.4,1.06,1.09,
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,,24.04,21.08,,33.55,32.81,20.47,32.77,29.82
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,,3927,2886.12,,2946.97,2952.76,2496.52,2595.65,
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,,3911.97,2881.04,,2975.15,2948.39,2493.98,2547.35,
"OpenCV - Test: Stitching (ms)",LIB,,201160,184032,,,287492,,232977,228123
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,,2608.34,1935.6,,2013.52,2020.21,1684.86,1782.06,
"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 (ms)",LIB,,230.27,172.53,,182.1,180.91,151.73,162.5,
"ASKAP - Test: tConvolve MT - Degridding (Million Grid Points/sec)",HIB,,8308.33,9611.05,,12506.7,11068.8,10352.6,11891.4,12025.7
"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
"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
"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: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,,1175.01,886.41,,914.24,912.42,821.36,826.77,
"ASKAP - Test: tConvolve OpenMP - Degridding (Million Grid Points/sec)",HIB,,19018.3,19018.3,,16641,15662.1,14792,13312.8,13312.8
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,,26.54,19,,19.58,19.69,19.99,20.33,
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,,16.93,12.84,,12.76,12.79,12.26,12.54,
"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
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,,16.93,12.77,,12.66,12.66,13.36,13.52,
"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
"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
"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
"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
"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: Live (sec)",LIB,47.74,47.206774889,45.71,45.79,54.58,47.07,44.06,45.467307319,50.590873871
"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
"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
"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
"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
"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 - Compression Speed (MB/s)",HIB,,988.5,1067.8,,1024,1013.4,913.5,1022.3,992.4
"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
"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
"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
"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
"NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,,133.39,126.26,,144.31,145.49,140.06,145.33,144.55
"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: 19, Long Mode - Decompression Speed (MB/s)",HIB,,1190.8,1229.1,,1222.9,1227.1,1312.9,1289.9,1292.1
"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: 19 - Decompression Speed (MB/s)",HIB,,1276.8,1304.2,,1315.6,1312,1389.6,1375.8,1394.3
"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: 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 - 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: 3 - Decompression Speed (MB/s)",HIB,,1277.3,1326.5,,1306.7,1309.5,1281.1,1384.1,1362.4
"Zstd Compression - Compression Level: 12 - Decompression Speed (MB/s)",HIB,,1445.9,1478.1,,1482.7,1498.9,1557.2,1563,1552
"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
"QuantLib - (MFLOPS)",HIB,2746.5,2692.4,2756.9,2820.4,2760.9,2850.8,2854.1,2894.2,2907.3
"Google Draco - Model: Church Facade (ms)",LIB,5793,5833,5718,,5682,5729,5406,5498,5485
"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
"Zstd Compression - Compression Level: 3 - Compression Speed (MB/s)",HIB,,2819,2856.6,,2783.7,2775.9,2661,2842.3,2801.4
"Google Draco - Model: Lion (ms)",LIB,4867,4885,4760,,4734,4818,4563,4642,4614
"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: Platform (sec)",LIB,173.23,172.56956694,162.19,,170.942711463,173.56002958,162.296027345,169.985789453,165.700132761
"eSpeak-NG Speech Engine - Text-To-Speech Synthesis (sec)",LIB,,28.157,27.826,,27.868,28.137,26.507,26.467,26.514
"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: Upload (sec)",LIB,116.93,116.80915814,110.01,110.14,112.819760537,114.261775562,110.605502327,113.672822126,112.961052185
"Z3 Theorem Prover - SMT File: 1.smt2 (sec)",LIB,,,,,,,,21.218,21.717
"Z3 Theorem Prover - SMT File: 2.smt2 (sec)",LIB,,,,,,,,70.286,70.51