Intel Core i5-5300U testing with a HP 2216 (M71 Ver. 01.27 BIOS) and Intel HD 5500 3GB on Ubuntu 20.04 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 2008300-FI-COREI5LAP35
Core i5 Laptop,
"oneDNN 1.5 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",10.8462,10.6905,10.7686
"Run 2",10.298,10.2244,10.241
"Run 3",11.2484,10.3869,10.2578,10.3666,10.7872,11.4714,11.5023,11.6427,11.1586,10.9705,11.045,10.9144,11.2288,11.3895,11.6205
"Rodinia 3.1 - Test: OpenMP CFD Solver",
Lower Results Are Better
"Run 1",123.722,125.387,124.105
"Run 2",115.099,116.401,118.682
"Run 3",117.716,116.599,114.047
"oneDNN 1.5 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",1531.98,1530.57,1600.75
"Run 2",1544.61,1513.74,1538.18
"Run 3",1692.9,1533.4,1694.56,1622.84,1687.01,1560.55,1718.74,1558.73,1556.37,1682.98,1574.31,1559.61,1556.4,1742.98,1686.39
"oneDNN 1.5 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",34.643,35.0491,35.09
"Run 2",33.5915,33.8046,34.0428
"Run 3",35.207,35.3123,34.7667
"ECP-CANDLE 0.3 - Benchmark: P1B2",
Lower Results Are Better
"Run 1",
"Run 2",
"Run 3",
"libavif avifenc 0.7.3 - Encoder Speed: 0",
Lower Results Are Better
"Run 1",494.899,495.893,477.634
"Run 2",478.091,476.841,476.022
"Run 3",476.439,477.788,477.199
"oneDNN 1.5 - Harness: IP Batch All - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",308.427,307.256,305.586
"Run 2",303.241,305.151,303.668
"Run 3",314.284,309.512,310.415
"oneDNN 1.5 - Harness: IP Batch 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",23.2945,23.9319,22.6628
"Run 2",22.8504,22.8261,23.0288
"Run 3",22.6302,22.9285,22.7732
"oneDNN 1.5 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",808.908,806.074,817.231
"Run 2",800.207,824.306,809.463
"Run 3",821.667,833.72,817.687
"ECP-CANDLE 0.3 - Benchmark: P3B1",
Lower Results Are Better
"Run 1",
"Run 2",
"Run 3",
"Timed Apache Compilation 2.4.41 - Time To Compile",
Lower Results Are Better
"Run 1",74.218,74.423,74.235
"Run 2",73.825,73.988,73.825
"Run 3",74.934,74.807,74.872
"Geekbench 5 - Test: CPU Single Core - Face Detection",
Higher Results Are Better
"Run 1",5.73,5.9,5.95
"Run 2",5.91,5.91,5.95
"Run 3",5.89,5.89,5.89
"Timed Linux Kernel Compilation 5.4 - Time To Compile",
Lower Results Are Better
"Run 1",569.99,566.582,566.738
"Run 2",566.754,562.6,563.739
"Run 3",572.357,568.791,568.808
"libavif avifenc 0.7.3 - Encoder Speed: 2",
Lower Results Are Better
"Run 1",284.74,284.326,285.758
"Run 2",283.273,283.171,283.536
"Run 3",282.595,282.714,282.674
"Rodinia 3.1 - Test: OpenMP HotSpot3D",
Lower Results Are Better
"Run 1",228.858,225.931,225.787
"Run 2",227.3,225.765,224.047
"Run 3",227.26,228.02,227.238
"Geekbench 5 - Test: CPU Multi Core - Face Detection",
Higher Results Are Better
"Run 1",12.7,12.7,12.7
"Run 2",12.6,12.6,12.7
"Run 3",12.7,12.7,12.6
"Geekbench 5 - Test: CPU Multi Core - Horizon Detection",
Higher Results Are Better
"Run 1",43.2,43.1,43.2
"Run 2",42.5,43,43.2
"Run 3",43.1,43.1,43.1
"Rodinia 3.1 - Test: OpenMP Streamcluster",
Lower Results Are Better
"Run 1",47.039,47.101,47.094
"Run 2",46.735,46.81,46.832
"Run 3",46.928,47.06,47.077
"oneDNN 1.5 - Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",37.809,37.8494,38.1635
"Run 2",37.7127,37.7581,37.7151
"Run 3",37.7665,37.8832,37.8761
"Darmstadt Automotive Parallel Heterogeneous Suite - Backend: OpenMP - Kernel: Points2Image",
Higher Results Are Better
"Run 1",14155.383646285,14223.199935521,14203.032347406
"Run 2",14184.430696054,14201.317882299,14205.487106153
"Run 3",14106.826293243,14114.259636511,14133.210217369
"Geekbench 5 - Test: CPU Single Core - Horizon Detection",
Higher Results Are Better
"Run 1",19.2,19.3,19.4
"Run 2",19.2,19.1,19.4
"Run 3",19.2,19.3,19.3
"Geekbench 5 - Test: CPU Single Core",
Higher Results Are Better
"Run 1",790,788,788
"Run 2",786,784,785
"Run 3",784,784,787
"oneDNN 1.5 - Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",27.9363,27.8817,27.7527
"Run 2",27.6987,27.7843,27.7834
"Run 3",27.6148,27.9809,27.7316
"Rodinia 3.1 - Test: OpenMP Leukocyte",
Lower Results Are Better
"Run 1",644.104,644.311,648.408
"Run 2",645.587,641.651,642.623
"Run 3",644.041,641.519,644.46
"TensorFlow Lite 2020-08-23 - Model: Mobilenet Quant",
Lower Results Are Better
"Run 1",944220,945113,953234
"Run 2",944584,945366,944824
"Run 3",944134,945033,944462
"Darmstadt Automotive Parallel Heterogeneous Suite - Backend: OpenMP - Kernel: Euclidean Cluster",
Higher Results Are Better
"Run 1",436.02116156037,437.19669479299,437.4166174573
"Run 2",435.04111138503,437.34009752684,437.35603697116
"Run 3",435.58433638726,435.65707979059,435.54955465058
"Geekbench 5 - Test: CPU Multi Core - Gaussian Blur",
Higher Results Are Better
"Run 1",77.4,77.9,78
"Run 2",77.9,77.6,77.4
"Run 3",77.5,78.1,77.7
"Geekbench 5 - Test: CPU Multi Core",
Higher Results Are Better
"Run 1",1636,1632,1632
"Run 2",1627,1634,1628
"Run 3",
"Montage Astronomical Image Mosaic Engine 6.0 - Mosaic of M17, K band, 1.5 deg x 1.5 deg",
Lower Results Are Better
"Run 1",121.977,122.213,121.844
"Run 2",122.361,122.063,122.245
"Run 3",122.151,121.992,122.076
"ASTC Encoder 2.0 - Preset: Thorough",
Lower Results Are Better
"Run 1",196.26,195.96,196.38
"Run 2",196.82,196.16,196.34
"Run 3",196.28,196.11,196.13
"ASTC Encoder 2.0 - Preset: Medium",
Lower Results Are Better
"Run 1",28.61,28.64,28.64
"Run 2",28.62,28.66,28.68
"Run 3",28.61,28.63,28.62
"libavif avifenc 0.7.3 - Encoder Speed: 10",
Lower Results Are Better
"Run 1",14.738,14.752,14.713
"Run 2",14.698,14.774,14.748
"Run 3",14.757,14.765,14.725
"TensorFlow Lite 2020-08-23 - Model: Inception V4",
Lower Results Are Better
"Run 1",20825800,20823500,20834500
"Run 2",20830000,20828600,20886500
"Run 3",20837300,20881700,20825100
"ASTC Encoder 2.0 - Preset: Fast",
Lower Results Are Better
"Run 1",10.48,10.5,10.5
"Run 2",10.49,10.49,10.5
"Run 3",10.5,10.5,10.49
"ASTC Encoder 2.0 - Preset: Exhaustive",
Lower Results Are Better
"Run 1",1599.21,1598.83,1602.95
"Run 2",1601.89,1601.34,1601.08
"Run 3",1601.75,1602.89,1600.04
"Darmstadt Automotive Parallel Heterogeneous Suite - Backend: OpenMP - Kernel: NDT Mapping",
Higher Results Are Better
"Run 1",427.3747791897,428.06692112867,427.58492905653
"Run 2",426.95813675469,427.66721788219,428.0394367001
"Run 3",427.30781830872,429.29816904331,426.99763727974
"NAMD 2.14 - ATPase Simulation - 327,506 Atoms",
Lower Results Are Better
"Run 1",11.1019,11.1327,11.1554
"Run 2",11.1356,11.1297,11.1462
"Run 3",11.1164,11.1678,11.1038
"TensorFlow Lite 2020-08-23 - Model: NASNet Mobile",
Lower Results Are Better
"Run 1",1007600,1007080,1008060
"Run 2",1007150,1007830,1007980
"Run 3",1007910,1008410,1008310
"TensorFlow Lite 2020-08-23 - Model: SqueezeNet",
Lower Results Are Better
"Run 1",1439630,1439600,1440280
"Run 2",1439940,1441780,1439830
"Run 3",1439760,1439730,1439660
"libavif avifenc 0.7.3 - Encoder Speed: 8",
Lower Results Are Better
"Run 1",16.609,16.641,16.675
"Run 2",16.651,16.626,16.647
"Run 3",16.618,16.672,16.655
"TensorFlow Lite 2020-08-23 - Model: Inception ResNet V2",
Lower Results Are Better
"Run 1",18854400,18849800,18851800
"Run 2",18846900,18846700,18862300
"Run 3",18856800,18851900,18850900
"TensorFlow Lite 2020-08-23 - Model: Mobilenet Float",
Lower Results Are Better
"Run 1",976342,976860,976524
"Run 2",976508,976566,976813
"Run 3",976516,976546,976749
"Geekbench 5 - Test: CPU Single Core - Gaussian Blur",
Higher Results Are Better
"Run 1",34,34.3,30
"Run 2",31.4,32.6,32.4
"Run 3",31.3,31.5,32.4
"Rodinia 3.1 - Test: OpenMP LavaMD",
Lower Results Are Better
"Run 1",1838.636,1841.264,1836.601
"Run 2",2416.696,1989.739,1837.335,1839.259,1836.321,1838.81,1837.999,1836.734,1836.159
"Run 3",1838.811,1841.265,1844.466