AMD EPYC 9684X 96-Core testing with a AMD Titanite_4G (RTI1007B BIOS) and ASPEED 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 2307207-NE-UPLOAD92587
AMD EPYC 9684X 3D V-Cache,
"Stress-NG 0.15.10 - Test: x86_64 RdRand",
"Default",
"Stress-NG 0.15.10 - Test: Hash",
Higher Results Are Better
"Default",18746919.86,18753317.34,18739684.46
"Stress-NG 0.15.10 - Test: MMAP",
Higher Results Are Better
"Default",1446.32,1444.84,1443.61
"Stress-NG 0.15.10 - Test: NUMA",
Higher Results Are Better
"Default",2479.84,2466.84,2488.95
"Stress-NG 0.15.10 - Test: Pipe",
Higher Results Are Better
"Default",59322292.85,61430058.74,60156386.41
"Stress-NG 0.15.10 - Test: Poll",
Higher Results Are Better
"Default",13254791.98,13274764.52,13277733.36
"Stress-NG 0.15.10 - Test: Zlib",
Higher Results Are Better
"Default",10474.25,10473.7,10465.57
"Stress-NG 0.15.10 - Test: Futex",
Higher Results Are Better
"Default",4008510.23,3960880.75,3987737.7
"Stress-NG 0.15.10 - Test: MEMFD",
Higher Results Are Better
"Default",453.82,454.02,456.4
"Stress-NG 0.15.10 - Test: Mutex",
Higher Results Are Better
"Default",49504282.89,50024269.94,49679801.36
"Stress-NG 0.15.10 - Test: Atomic",
Higher Results Are Better
"Default",237.88,237.72,237.88
"Stress-NG 0.15.10 - Test: Crypto",
Higher Results Are Better
"Default",202547.29,201538.48,203020.07
"Stress-NG 0.15.10 - Test: Malloc",
Higher Results Are Better
"Default",360664574.35,361002878.18,359379546.43
"Stress-NG 0.15.10 - Test: Cloning",
Higher Results Are Better
"Default",18072.9,12795.02,15930.96,13709.19,11297.64,16026.06,11049.66,10585.32,14048.91,10737.72,9985.96,5505.54
"Stress-NG 0.15.10 - Test: Forking",
Higher Results Are Better
"Default",40493.32,40446.91,40262.25
"Stress-NG 0.15.10 - Test: Pthread",
Higher Results Are Better
"Default",102395.85,103230.68,104215.83
"Stress-NG 0.15.10 - Test: AVL Tree",
Higher Results Are Better
"Default",1665.2,1665.14,1666.38
"Stress-NG 0.15.10 - Test: IO_uring",
Higher Results Are Better
"Default",5532054.6,6010420.48,6706531.11,7564590.54,7594335.95,3749748.2,2693283.86,2039894.66,2485645.11,2798051.33,5169442.32,5141139.76
"Stress-NG 0.15.10 - Test: SENDFILE",
Higher Results Are Better
"Default",821000.89,809182.91,913144.98,1634335.86,1760158.55,1746574.48,1747903.96,1749991.98,1754847.48,1752252.53,1756206.34,1759166.07
"Stress-NG 0.15.10 - Test: CPU Cache",
Higher Results Are Better
"Default",1417132.81,1397369.82,1378221.61
"Stress-NG 0.15.10 - Test: CPU Stress",
Higher Results Are Better
"Default",212303.53,212019.7,212819.06
"Stress-NG 0.15.10 - Test: Semaphores",
Higher Results Are Better
"Default",227224772.65,221619059.66,220797987.26
"Stress-NG 0.15.10 - Test: Matrix Math",
Higher Results Are Better
"Default",418102.42,418098.16,417898.8
"Stress-NG 0.15.10 - Test: Vector Math",
Higher Results Are Better
"Default",545611.3,545745.51,545820.37
"Stress-NG 0.15.10 - Test: Function Call",
Higher Results Are Better
"Default",67362.36,67258.9,67318.9
"Stress-NG 0.15.10 - Test: Floating Point",
Higher Results Are Better
"Default",29877.51,29859.56,29914.72
"Stress-NG 0.15.10 - Test: Matrix 3D Math",
Higher Results Are Better
"Default",16765.13,16734.27,16286.44
"Stress-NG 0.15.10 - Test: Memory Copying",
Higher Results Are Better
"Default",32992.45,32993.54,32996.54
"Stress-NG 0.15.10 - Test: Vector Shuffle",
Higher Results Are Better
"Default",63755.85,63766.65,63761.37
"Stress-NG 0.15.10 - Test: Socket Activity",
Higher Results Are Better
"Default",8998.68,17.12,7.16,8734.07,7.09,24.01,7.13,8736.06,18.25,7.36,8830,7.23,29.14,166.16,8814.15
"Stress-NG 0.15.10 - Test: Wide Vector Math",
Higher Results Are Better
"Default",3486542.55,3483461.35,3486119.08
"Stress-NG 0.15.10 - Test: Context Switching",
Higher Results Are Better
"Default",16831651.28,13700219.16,15828030.98,17939127.98,15714164.95,18146770.56,14522517.62,18314120.45,10408572.66,16167431.63,15936566.63,17312264.63,17553299.52,12354799.03,11479488.02
"Stress-NG 0.15.10 - Test: Fused Multiply-Add",
Higher Results Are Better
"Default",76553329.99,76545144.47,76601256.91
"Stress-NG 0.15.10 - Test: Vector Floating Point",
Higher Results Are Better
"Default",258182.44,257935.67,257658.71
"Stress-NG 0.15.10 - Test: Glibc C String Functions",
Higher Results Are Better
"Default",80642674.72,80751031.36,82230474.44
"Stress-NG 0.15.10 - Test: Glibc Qsort Data Sorting",
Higher Results Are Better
"Default",2109.29,2107.53,2108.08
"Stress-NG 0.15.10 - Test: System V Message Passing",
Higher Results Are Better
"Default",12095862.5,12082839.96,12077579.21
"miniFE 2.2 - Problem Size: Small",
Higher Results Are Better
"Default",55241.7,54555.9,54109.4,54069.2,54064.7
"Algebraic Multi-Grid Benchmark 1.2 - ",
Higher Results Are Better
"Default",2416217000,2421183000,2405449000
"OpenVINO 2022.3 - Model: Face Detection FP16 - Device: CPU",
Higher Results Are Better
"Default",47.61,47.6,47.66
"OpenVINO 2022.3 - Model: Person Detection FP16 - Device: CPU",
Higher Results Are Better
"Default",27.3,26.94,27.09
"OpenVINO 2022.3 - Model: Person Detection FP32 - Device: CPU",
Higher Results Are Better
"Default",26.69,26.95,27.04
"OpenVINO 2022.3 - Model: Vehicle Detection FP16 - Device: CPU",
Higher Results Are Better
"Default",3860.61,3861.17,3860.14
"OpenVINO 2022.3 - Model: Face Detection FP16-INT8 - Device: CPU",
Higher Results Are Better
"Default",90.38,90.35,90.36
"OpenVINO 2022.3 - Model: Vehicle Detection FP16-INT8 - Device: CPU",
Higher Results Are Better
"Default",5671.41,5672.74,5672.04
"OpenVINO 2022.3 - Model: Weld Porosity Detection FP16 - Device: CPU",
Higher Results Are Better
"Default",4663.97,4663.63,4664.3
"OpenVINO 2022.3 - Model: Machine Translation EN To DE FP16 - Device: CPU",
Higher Results Are Better
"Default",537.05,534.57,535.69
"OpenVINO 2022.3 - Model: Weld Porosity Detection FP16-INT8 - Device: CPU",
Higher Results Are Better
"Default",8846.7,8846.45,8846.86
"OpenVINO 2022.3 - Model: Person Vehicle Bike Detection FP16 - Device: CPU",
Higher Results Are Better
"Default",5734.69,5726.94,5736.61
"OpenVINO 2022.3 - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU",
Higher Results Are Better
"Default",94395.19,94588.89,94531.26
"OpenVINO 2022.3 - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU",
Higher Results Are Better
"Default",64567.9,64469.55,64348.34
"Embree 4.1 - Binary: Pathtracer ISPC - Model: Crown",
Higher Results Are Better
"Default",117.9722,117.8651,118.0871,117.7053,117.4393,117.8895,117.8242
"Embree 4.1 - Binary: Pathtracer ISPC - Model: Asian Dragon",
Higher Results Are Better
"Default",143.6114,143.8753,144.2361,144.1413,143.7327,144.3749,143.9958
"Embree 4.1 - Binary: Pathtracer ISPC - Model: Asian Dragon Obj",
Higher Results Are Better
"Default",123.5487,123.5213,123.6159,123.368
"High Performance Conjugate Gradient 3.1 - X Y Z: 104 104 104 - RT: 60",
Higher Results Are Better
"Default",31.8493,23.6143,28.0758,25.8791,23.9515,27.4894,26.3151,27.8925,26.3576
"High Performance Conjugate Gradient 3.1 - X Y Z: 144 144 144 - RT: 60",
Higher Results Are Better
"Default",24.8168,27.4227,24.0797,25.9779,24.454,23.2618,23.4063,23.9902,24.119
"High Performance Conjugate Gradient 3.1 - X Y Z: 160 160 160 - RT: 60",
Higher Results Are Better
"Default",24.477,23.3117,23.722
"High Performance Conjugate Gradient 3.1 - X Y Z: 192 192 192 - RT: 60",
Higher Results Are Better
"Default",23.0494,22.4864,22.9637
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128",
Higher Results Are Better
"Default",125.879,123.17,128.691,125.41,128.768,124.163,127.94,128.334,124.159,128.055,129.321,120.334,124.146
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256",
Higher Results Are Better
"Default",181.513,174.176,180.211,180.179,180.325,184.789,177.283,172.277,177.365,178.55,176.181
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512",
Higher Results Are Better
"Default",154.736,154.768,151.289,154.582
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128",
Higher Results Are Better
"Default",185.105,185.711,185.886,185.271,188.035,185.797,182.483,184.903,183.37,187.921,184.09,185.637,185.853
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256",
Higher Results Are Better
"Default",310.987,319.869,322.55,313.997,314.781,317.85,314.555,316.085,319.66,313.387,312.646,313.393
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512",
Higher Results Are Better
"Default",334.293,334.511,329.874,340.291,328.031,329.449
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128",
Higher Results Are Better
"Default",79.4434,80.1581,79.8444,80.8134,80.1844,78.9145,79.6845,80.7968,77.3876,82.0491,79.904,80.2022,79.6265
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256",
Higher Results Are Better
"Default",87.9764,87.0907,85.2954,85.7754,89.4032,86.1221,88.9362,85.1091,87.6443
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512",
Higher Results Are Better
"Default",67.9436,67.6573,67.9501
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128",
Higher Results Are Better
"Default",128.028,129.968,129.585,127.194,132.682,131.863,130.005,129.938,133.135,129.837,130.515,129.102,126.519
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256",
Higher Results Are Better
"Default",196.714,196.139,188.309,193.571,191.435,183.027,185.244,200.557,184.534,188.359,197.58,190.841,181.922,186.794,186.862
"HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512",
Higher Results Are Better
"Default",133.736,133.902,135.814,135.826
"ACES DGEMM 1.0 - Sustained Floating-Point Rate",
Higher Results Are Better
"Default",40.811267,40.635673,39.875215,40.948604,40.427672,40.592638,40.581192
"libxsmm 2-1.17-3645 - M N K: 128",
Higher Results Are Better
"Default",3065,2864.4,3051.7,2887.6,2861.9,2875.7,2874.3,2899.4,2840.3
"libxsmm 2-1.17-3645 - M N K: 256",
Higher Results Are Better
"Default",2986.2,2982,3126.7,3109,3118.3
"libxsmm 2-1.17-3645 - M N K: 32",
Higher Results Are Better
"Default",1313.7,1313.7,1310.6,1308.1,1314.3,1311.6,1302.2,1316.3
"libxsmm 2-1.17-3645 - M N K: 64",
Higher Results Are Better
"Default",2458,2470.2,2449,2458.8,2466.3,2434.2,2451.4
"Xmrig 6.18.1 - Variant: Monero - Hash Count: 1M",
Higher Results Are Better
"Default",69671.8,69832.4,69454.1,69778.8
"Xmrig 6.18.1 - Variant: Wownero - Hash Count: 1M",
Higher Results Are Better
"Default",74074.1,74002.8,73997.3,73964.5
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: AlexNet",
Higher Results Are Better
"Default",304.28,303.74,304.88,302.85,301.99,305.06
"TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: AlexNet",
Higher Results Are Better
"Default",518.58,518.52,518.58,515.71,519.36
"TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: AlexNet",
Higher Results Are Better
"Default",791.99,788.11,789.62,783.7,779.57
"TensorFlow 2.12 - Device: CPU - Batch Size: 256 - Model: AlexNet",
Higher Results Are Better
"Default",1196.75,1196.51,1195.23
"TensorFlow 2.12 - Device: CPU - Batch Size: 512 - Model: AlexNet",
Higher Results Are Better
"Default",1287.7,1289.01,1286.71
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: GoogLeNet",
Higher Results Are Better
"Default",156.91,156.8,157.99,156.06
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"Default",57.35,56.8,57.48
"TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: GoogLeNet",
Higher Results Are Better
"Default",238.58,238.38,237.58
"TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"Default",78.28,78.29,77.75
"TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: GoogLeNet",
Higher Results Are Better
"Default",296.14,296.18,296.25
"TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"Default",94.47,94.37,94.66
"TensorFlow 2.12 - Device: CPU - Batch Size: 256 - Model: GoogLeNet",
Higher Results Are Better
"Default",388.16,386.89,387.99
"TensorFlow 2.12 - Device: CPU - Batch Size: 256 - Model: ResNet-50",
Higher Results Are Better
"Default",123.25,113.57,114.3,113.59,114.6,114.82,114.25,116.09,115.11
"TensorFlow 2.12 - Device: CPU - Batch Size: 512 - Model: GoogLeNet",
Higher Results Are Better
"Default",448.44,418.75,402.61,405.13,405.58,401.96,403.72,402.08,407.1,405.9,401.46,405.47
"TensorFlow 2.12 - Device: CPU - Batch Size: 512 - Model: ResNet-50",
Higher Results Are Better
"Default",118,115.23,115.22
"OSPRay 2.12 - Benchmark: particle_volume/ao/real_time",
Higher Results Are Better
"Default",25.149,25.1475,25.1749
"OSPRay 2.12 - Benchmark: particle_volume/scivis/real_time",
Higher Results Are Better
"Default",25.1039,25.1268,25.0957
"OSPRay 2.12 - Benchmark: particle_volume/pathtracer/real_time",
Higher Results Are Better
"Default",199.64,199.576,199.869
"OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/ao/real_time",
Higher Results Are Better
"Default",26.7803,26.9978,26.5987
"OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time",
Higher Results Are Better
"Default",25.848,25.9599,25.9736
"OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time",
Higher Results Are Better
"Default",26.5177,26.5429,26.4828
"Neural Magic DeepSparse 1.5 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",60.6323,60.5825,60.6772
"Neural Magic DeepSparse 1.5 - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",1219.1146,1218.1731,1221.1997
"Neural Magic DeepSparse 1.5 - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",329.4821,330.2025,330.2474
"Neural Magic DeepSparse 1.5 - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",344.2505,343.7848,345.1805
"Neural Magic DeepSparse 1.5 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",797.122,798.7178,798.0016
"Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",512.6421,513.6785,513.2387
"Neural Magic DeepSparse 1.5 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",114.0944,114.1231,114.3156
"Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",257.4711,257.571,257.6714
"Neural Magic DeepSparse 1.5 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream",
Higher Results Are Better
"Default",60.5526,60.6019,60.5976
"ASKAP 1.0 - Test: Hogbom Clean OpenMP",
Higher Results Are Better
"Default",1219.51,1219.51,1204.82,1204.82
"Laghos 3.1 - Test: Triple Point Problem",
Higher Results Are Better
"Default",241.24464158,239.7116226518,235.7156902041
"Laghos 3.1 - Test: Sedov Blast Wave, ube_922_hex.mesh",
Higher Results Are Better
"Default",444.4330173459,449.6706623188,446.6781627178
"Zstd Compression 1.5.4 - Compression Level: 3 - Compression Speed",
Higher Results Are Better
"Default",4003.9,3945.6,4019.5
"Zstd Compression 1.5.4 - Compression Level: 3 - Decompression Speed",
Higher Results Are Better
"Default",1496.5,1499.8,1500.2
"Zstd Compression 1.5.4 - Compression Level: 8 - Compression Speed",
Higher Results Are Better
"Default",1226.8,1223.9,1229.3
"Zstd Compression 1.5.4 - Compression Level: 8 - Decompression Speed",
Higher Results Are Better
"Default",1635.4,1641.7,1642.5
"Zstd Compression 1.5.4 - Compression Level: 12 - Compression Speed",
Higher Results Are Better
"Default",328.7,326.7,332.6
"Zstd Compression 1.5.4 - Compression Level: 12 - Decompression Speed",
Higher Results Are Better
"Default",1657.4,1651.7,1650.9
"Zstd Compression 1.5.4 - Compression Level: 19 - Compression Speed",
Higher Results Are Better
"Default",17.2,17.3,17.3
"Zstd Compression 1.5.4 - Compression Level: 19 - Decompression Speed",
Higher Results Are Better
"Default",1420.8,1439.1,1440.2
"Zstd Compression 1.5.4 - Compression Level: 3, Long Mode - Compression Speed",
Higher Results Are Better
"Default",912.3,884.1,873.2
"Zstd Compression 1.5.4 - Compression Level: 3, Long Mode - Decompression Speed",
Higher Results Are Better
"Default",1531.8,1532.4,1539.3
"Zstd Compression 1.5.4 - Compression Level: 8, Long Mode - Compression Speed",
Higher Results Are Better
"Default",882.9,877.1,870.6
"Zstd Compression 1.5.4 - Compression Level: 8, Long Mode - Decompression Speed",
Higher Results Are Better
"Default",1648.1,1649.2,1647
"Zstd Compression 1.5.4 - Compression Level: 19, Long Mode - Compression Speed",
Higher Results Are Better
"Default",8.52,8.49,8.54
"Zstd Compression 1.5.4 - Compression Level: 19, Long Mode - Decompression Speed",
Higher Results Are Better
"Default",1360.6,1353.2,1359.7
"PETSc 3.19 - Test: Streams",
Higher Results Are Better
"Default",278065.8872,279152.6759,224901.0766,280459.5995,281195.6244,276104.1351,274390.2926,279140.4979,280141.4058
"srsRAN Project 23.5 - Test: Downlink Processor Benchmark",
Higher Results Are Better
"Default",727.8,707.8,728.2
"srsRAN Project 23.5 - Test: PUSCH Processor Benchmark, Throughput Total",
Higher Results Are Better
"Default",18369,18406.5,18448.9
"Palabos 2.3 - Grid Size: 100",
Higher Results Are Better
"Default",600.669,586.634,587.298
"Palabos 2.3 - Grid Size: 400",
Higher Results Are Better
"Default",349.073,314.512,315.253,313.973,314.264,313.978,317.423,315.404,314.648,313.814,315.168,316.334
"Palabos 2.3 - Grid Size: 500",
Higher Results Are Better
"Default",328.604,328.919,328.616
"Palabos 2.3 - Grid Size: 1000",
Higher Results Are Better
"Default",370.387,370.116,370.065
"ASKAP 1.0 - Test: tConvolve MT - Gridding",
Higher Results Are Better
"Default",13581.6,13585.2,13581.6
"ASKAP 1.0 - Test: tConvolve MT - Degridding",
Higher Results Are Better
"Default",15571.5,15609.5,15628.6
"ASKAP 1.0 - Test: tConvolve OpenMP - Gridding",
Higher Results Are Better
"Default",26625.6,26625.6,26625.6,26625.6,26625.6,26625.6,26625.6
"ASKAP 1.0 - Test: tConvolve OpenMP - Degridding",
Higher Results Are Better
"Default",53251.2,53251.2,53251.2,66564,53251.2,53251.2,53251.2
"7-Zip Compression 22.01 - Test: Compression Rating",
Higher Results Are Better
"Default",647984,646441,646764
"7-Zip Compression 22.01 - Test: Decompression Rating",
Higher Results Are Better
"Default",627369,624379,627668
"ASKAP 1.0 - Test: tConvolve MPI - Degridding",
Higher Results Are Better
"Default",60552.8,59410.3,59410.3
"ASKAP 1.0 - Test: tConvolve MPI - Gridding",
Higher Results Are Better
"Default",73226.7,73226.7,73226.7
"ASTC Encoder 4.0 - Preset: Medium",
Higher Results Are Better
"Default",419.1702,419.537,419.4339,419.6017,419.2575,419.5807,419.3762,419.4549
"ASTC Encoder 4.0 - Preset: Thorough",
Higher Results Are Better
"Default",56.8683,56.7633,56.7986,56.7147,56.7708,56.7524
"ASTC Encoder 4.0 - Preset: Exhaustive",
Higher Results Are Better
"Default",6.1434,6.1441,6.1404,6.1365
"LeelaChessZero 0.28 - Backend: BLAS",
Higher Results Are Better
"Default",9749,10107,9467,9688,9788
"LeelaChessZero 0.28 - Backend: Eigen",
Higher Results Are Better
"Default",11784,12025,11843
"Stockfish 15 - Total Time",
Higher Results Are Better
"Default",298525568,295206762,298137346
"asmFish 2018-07-23 - 1024 Hash Memory, 26 Depth",
Higher Results Are Better
"Default",235681806,234990593,231450210
"GROMACS 2023 - Implementation: MPI CPU - Input: water_GMX50_bare",
Higher Results Are Better
"Default",11.772,11.796,11.811
"LAMMPS Molecular Dynamics Simulator 23Jun2022 - Model: 20k Atoms",
Higher Results Are Better
"Default",39.961,39.961,39.758
"Liquid-DSP 1.6 - Threads: 64 - Buffer Length: 256 - Filter Length: 32",
Higher Results Are Better
"Default",2181600000,2182800000,2179400000
"Liquid-DSP 1.6 - Threads: 64 - Buffer Length: 256 - Filter Length: 57",
Higher Results Are Better
"Default",2626900000,2587500000,2614000000
"Liquid-DSP 1.6 - Threads: 128 - Buffer Length: 256 - Filter Length: 32",
Higher Results Are Better
"Default",3765800000,3770400000,3770000000
"Liquid-DSP 1.6 - Threads: 128 - Buffer Length: 256 - Filter Length: 57",
Higher Results Are Better
"Default",3871100000,3885700000,3873400000
"Liquid-DSP 1.6 - Threads: 192 - Buffer Length: 256 - Filter Length: 32",
Higher Results Are Better
"Default",4958500000,4958200000,4958900000
"Liquid-DSP 1.6 - Threads: 192 - Buffer Length: 256 - Filter Length: 57",
Higher Results Are Better
"Default",4630600000,4640500000,4632800000
"Liquid-DSP 1.6 - Threads: 64 - Buffer Length: 256 - Filter Length: 512",
Higher Results Are Better
"Default",727640000,731270000,723660000
"Liquid-DSP 1.6 - Threads: 128 - Buffer Length: 256 - Filter Length: 512",
Higher Results Are Better
"Default",1079400000,1082700000,1081200000
"Liquid-DSP 1.6 - Threads: 192 - Buffer Length: 256 - Filter Length: 512",
Higher Results Are Better
"Default",1287600000,1286700000,1289300000
"Numpy Benchmark - ",
Higher Results Are Better
"Default",588.41,585.33,585.76
"Kripke 1.2.6 - ",
Higher Results Are Better
"Default",
"NAS Parallel Benchmarks 3.4 - Test / Class: BT.C",
Higher Results Are Better
"Default",315423.66,308849.6,313909.41,317270.52,318436.3
"NAS Parallel Benchmarks 3.4 - Test / Class: CG.C",
Higher Results Are Better
"Default",62290.53,57728.99,60437.18,57373.28,60094.78,59738.04,58814.16,61073.08,59454.23,60375.14
"NAS Parallel Benchmarks 3.4 - Test / Class: EP.D",
Higher Results Are Better
"Default",10753.6,10578.1,10717.71,10742.2
"NAS Parallel Benchmarks 3.4 - Test / Class: FT.C",
Higher Results Are Better
"Default",119030.92,118856.2,118473.91,119474.57,118229.66,120551.5,117367.45,118670.91
"NAS Parallel Benchmarks 3.4 - Test / Class: IS.D",
Higher Results Are Better
"Default",5637.51,5762.12,5753.06,5712.43,5617.45
"NAS Parallel Benchmarks 3.4 - Test / Class: LU.C",
Higher Results Are Better
"Default",337695.99,334483.9,339207.51,338795.55,343221.71,334059.16
"NAS Parallel Benchmarks 3.4 - Test / Class: MG.C",
Higher Results Are Better
"Default",134892.9,141586.36,139919.17,148883.34,138672.53,132148.08,142822.26,144395.24,141918.46,136487.39,129491.59,137809.13,133484.58,132617.69,124495.38
"NAS Parallel Benchmarks 3.4 - Test / Class: SP.C",
Higher Results Are Better
"Default",204859.71,212234.42,205759.46,202806.9,207854.11,212173.61
"LULESH 2.0.3 - ",
Higher Results Are Better
"Default",30272.238,31134.395,30606.115,30848.564
"NAMD 2.14 - ATPase Simulation - 327,506 Atoms",
Lower Results Are Better
"Default",0.247545,0.247883,0.246562
"OSPRay Studio 0.11 - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer",
Lower Results Are Better
"Default",1057,1059,1061
"OSPRay Studio 0.11 - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer",
Lower Results Are Better
"Default",1063,1070,1063
"OSPRay Studio 0.11 - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer",
Lower Results Are Better
"Default",1261,1260,1261
"OSPRay Studio 0.11 - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer",
Lower Results Are Better
"Default",16956,16864,17038
"OSPRay Studio 0.11 - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer",
Lower Results Are Better
"Default",33962,34029,34031
"OSPRay Studio 0.11 - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer",
Lower Results Are Better
"Default",17071,17073,17090
"OSPRay Studio 0.11 - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer",
Lower Results Are Better
"Default",34242,34366,34415
"OSPRay Studio 0.11 - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer",
Lower Results Are Better
"Default",20273,20122,20275
"OSPRay Studio 0.11 - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer",
Lower Results Are Better
"Default",40382,40471,40323
"Google Draco 1.5.6 - Model: Lion",
Lower Results Are Better
"Default",5006,5018,5010,4996,5010,5018,5016
"Google Draco 1.5.6 - Model: Church Facade",
Lower Results Are Better
"Default",6037,6051,6030,6053,6051,6038
"OpenVINO 2022.3 - Model: Face Detection FP16 - Device: CPU",
Lower Results Are Better
"Default",1002.81,1003.94,1003.78
"OpenVINO 2022.3 - Model: Person Detection FP16 - Device: CPU",
Lower Results Are Better
"Default",1745.5,1761.58,1753.8
"OpenVINO 2022.3 - Model: Person Detection FP32 - Device: CPU",
Lower Results Are Better
"Default",1778.04,1766.71,1754.88
"OpenVINO 2022.3 - Model: Vehicle Detection FP16 - Device: CPU",
Lower Results Are Better
"Default",12.42,12.42,12.42
"OpenVINO 2022.3 - Model: Face Detection FP16-INT8 - Device: CPU",
Lower Results Are Better
"Default",529.63,529.77,529.64
"OpenVINO 2022.3 - Model: Vehicle Detection FP16-INT8 - Device: CPU",
Lower Results Are Better
"Default",8.45,8.45,8.45
"OpenVINO 2022.3 - Model: Weld Porosity Detection FP16 - Device: CPU",
Lower Results Are Better
"Default",10.28,10.28,10.28
"OpenVINO 2022.3 - Model: Machine Translation EN To DE FP16 - Device: CPU",
Lower Results Are Better
"Default",89.3,89.69,89.5
"OpenVINO 2022.3 - Model: Weld Porosity Detection FP16-INT8 - Device: CPU",
Lower Results Are Better
"Default",10.84,10.84,10.84
"OpenVINO 2022.3 - Model: Person Vehicle Bike Detection FP16 - Device: CPU",
Lower Results Are Better
"Default",8.36,8.37,8.36
"OpenVINO 2022.3 - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU",
Lower Results Are Better
"Default",0.84,0.84,0.84
"OpenVINO 2022.3 - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU",
Lower Results Are Better
"Default",1.33,1.33,1.32
"Neural Magic DeepSparse 1.5 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",785.1588,785.7377,779.831
"Neural Magic DeepSparse 1.5 - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",39.3147,39.3558,39.252
"Neural Magic DeepSparse 1.5 - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",145.1864,144.9478,145.029
"Neural Magic DeepSparse 1.5 - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",139.0018,139.2418,138.8035
"Neural Magic DeepSparse 1.5 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",60.1154,60.0272,60.0484
"Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",93.3598,93.2871,93.3219
"Neural Magic DeepSparse 1.5 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",418.4998,417.766,417.3094
"Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",185.844,185.9262,185.7816
"Neural Magic DeepSparse 1.5 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream",
Lower Results Are Better
"Default",785.4843,784.9448,785.2076
"CloverLeaf - Lagrangian-Eulerian Hydrodynamics",
Lower Results Are Better
"Default",10.258820056915,10.181025981903,10.365280151367,10.386933088303,10.276291847229
"Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 129 Cells Per Direction",
Lower Results Are Better
"Default",2.28146505,2.11254311,2.02710605,2.01774192,1.96271896,2.29640293,2.32221508,2.36860609,1.87706494,2.25977802,2.39050388,2.14338803,2.11148,2.36670589,2.09052205
"Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 193 Cells Per Direction",
Lower Results Are Better
"Default",7.60852814,7.585639,7.60309887,7.68593693,7.94323111
"Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 - Input: Gas HII40",
Lower Results Are Better
"Default",13.315,13.301,13.304,13.191
"Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 - Input: Dust 2D tau100.0",
Lower Results Are Better
"Default",187.959,188.828,193.425
"OpenFOAM 10 - Input: drivaerFastback, Large Mesh Size - Mesh Time",
Lower Results Are Better
"Default",
"OpenFOAM 10 - Input: drivaerFastback, Large Mesh Size - Execution Time",
Lower Results Are Better
"Default",
"OpenFOAM 10 - Input: drivaerFastback, Small Mesh Size - Mesh Time",
Lower Results Are Better
"Default",
"OpenFOAM 10 - Input: drivaerFastback, Small Mesh Size - Execution Time",
Lower Results Are Better
"Default",
"OpenFOAM 10 - Input: drivaerFastback, Medium Mesh Size - Mesh Time",
Lower Results Are Better
"Default",
"OpenFOAM 10 - Input: drivaerFastback, Medium Mesh Size - Execution Time",
Lower Results Are Better
"Default",
"Remhos 1.0 - Test: Sample Remap Example",
Lower Results Are Better
"Default",10.72,10.136,10.082,10.422,10.104,10.296
"SPECFEM3D 4.0 - Model: Mount St. Helens",
Lower Results Are Better
"Default",9.20960726,8.923758456,8.75023592,8.88881314,8.718311422
"SPECFEM3D 4.0 - Model: Layered Halfspace",
Lower Results Are Better
"Default",21.551501932,21.206968597,21.285437338
"SPECFEM3D 4.0 - Model: Tomographic Model",
Lower Results Are Better
"Default",8.656905801,8.814779746,8.736573526,8.715357962,8.770900888
"SPECFEM3D 4.0 - Model: Homogeneous Halfspace",
Lower Results Are Better
"Default",11.530033665,11.136632568,11.031943716,11.593950595
"SPECFEM3D 4.0 - Model: Water-layered Halfspace",
Lower Results Are Better
"Default",20.769458144,21.151657688,21.433038212
"Timed Gem5 Compilation 21.2 - Time To Compile",
Lower Results Are Better
"Default",137.491,136.558,139.023
"Timed Godot Game Engine Compilation 4.0 - Time To Compile",
Lower Results Are Better
"Default",88.509,88.296,88.346
"Timed Linux Kernel Compilation 6.1 - Build: defconfig",
Lower Results Are Better
"Default",23.926,22.637,22.675,22.768,22.588
"Timed Linux Kernel Compilation 6.1 - Build: allmodconfig",
Lower Results Are Better
"Default",203.495,202.689,201.486
"Timed LLVM Compilation 16.0 - Build System: Ninja",
Lower Results Are Better
"Default",112.39,113.446,112.824
"Timed LLVM Compilation 16.0 - Build System: Unix Makefiles",
Lower Results Are Better
"Default",182.202,185.92,184.018
"Timed Node.js Compilation 19.8.1 - Time To Compile",
Lower Results Are Better
"Default",105.387,104.921,105.374
"Timed PHP Compilation 8.1.9 - Time To Compile",
Lower Results Are Better
"Default",33.986,33.256,33.096
"Ngspice 34 - Circuit: C2670",
Lower Results Are Better
"Default",118.646,118.668,117.868
"Ngspice 34 - Circuit: C7552",
Lower Results Are Better
"Default",100.976,100.859,100.714
"WRF 4.2.2 - Input: conus 2.5km",
Lower Results Are Better
"Default",
"GPAW 23.6 - Input: Carbon Nanotube",
Lower Results Are Better
"Default",34.595,34.601,35.126
"Blender 3.6 - Blend File: BMW27 - Compute: CPU-Only",
Lower Results Are Better
"Default",16.26,16.11,16.46
"Blender 3.6 - Blend File: Classroom - Compute: CPU-Only",
Lower Results Are Better
"Default",40.36,40.46,40.72
"Blender 3.6 - Blend File: Fishy Cat - Compute: CPU-Only",
Lower Results Are Better
"Default",20.73,20.68,20.45
"Blender 3.6 - Blend File: Barbershop - Compute: CPU-Only",
Lower Results Are Better
"Default",142.04,142.04,142.02
"Blender 3.6 - Blend File: Pabellon Barcelona - Compute: CPU-Only",
Lower Results Are Better
"Default",49.55,49.52,49.77
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Equation of State",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Isoneutral Mixing",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Equation of State",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Isoneutral Mixing",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State",
Lower Results Are Better
"Default",0.766,0.762,0.774
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing",
Lower Results Are Better
"Default",1.579,1.577,1.578
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Equation of State",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Isoneutral Mixing",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Equation of State",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Isoneutral Mixing",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Equation of State",
Lower Results Are Better
"Default",
"PyHPC Benchmarks 3.0 - Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Isoneutral Mixing",
Lower Results Are Better
"Default",
"Whisper.cpp 1.4 - Model: ggml-base.en - Input: 2016 State of the Union",
Lower Results Are Better
"Default",335.11812,331.54709,329.38022
"Whisper.cpp 1.4 - Model: ggml-small.en - Input: 2016 State of the Union",
Lower Results Are Better
"Default",764.80456,766.86238,775.6745
"Whisper.cpp 1.4 - Model: ggml-medium.en - Input: 2016 State of the Union",
Lower Results Are Better
"Default",1444.26462,1454.08788,1434.055