august

AMD Ryzen 9 5950X 16-Core testing with a ASUS ROG CROSSHAIR VIII HERO (WI-FI) (4006 BIOS) and llvmpipe 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 2208052-NE-AUGUST46711
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August 04 2022
  1 Day, 10 Hours, 57 Minutes
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August 05 2022
  7 Hours, 21 Minutes
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August 05 2022
  7 Hours, 21 Minutes
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August 05 2022
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augustOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 5950X 16-Core @ 3.40GHz (16 Cores / 32 Threads)ASUS ROG CROSSHAIR VIII HERO (WI-FI) (4006 BIOS)AMD Starship/Matisse32GB1000GB Sabrent Rocket 4.0 PlusllvmpipeAMD Navi 21 HDMI AudioRealtek RTL8125 2.5GbE + Intel I211 + Intel Wi-Fi 6 AX200Ubuntu 22.045.15.0-40-generic (x86_64)GNOME Shell 42.2X Server 1.21.1.34.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits)1.2.204GCC 11.2.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionAugust BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa201016 - OpenJDK Runtime Environment (build 11.0.16+8-post-Ubuntu-0ubuntu122.04)- Python 3.10.4- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected

ABCDResult OverviewPhoronix Test Suite100%101%101%102%AI Benchmark AlphaSVT-AV1LAMMPS Molecular Dynamics SimulatorNode.js V8 Web Tooling BenchmarkInkscapePrimesieveApache SparkASTC Encoder

augustspark: 1000000 - 100 - Inner Join Test Timespark: 1000000 - 2000 - Broadcast Inner Join Test Timespark: 1000000 - 100 - Repartition Test Timespark: 1000000 - 1000 - SHA-512 Benchmark Timespark: 1000000 - 2000 - Inner Join Test Timespark: 10000000 - 2000 - Broadcast Inner Join Test Timespark: 40000000 - 1000 - Inner Join Test Timespark: 20000000 - 1000 - Broadcast Inner Join Test Timespark: 10000000 - 100 - Broadcast Inner Join Test Timespark: 20000000 - 2000 - Inner Join Test Timespark: 10000000 - 1000 - Inner Join Test Timespark: 1000000 - 1000 - Inner Join Test Timesvt-av1: Preset 12 - Bosphorus 4Kspark: 10000000 - 1000 - SHA-512 Benchmark Timespark: 1000000 - 2000 - Repartition Test Timespark: 40000000 - 500 - SHA-512 Benchmark Timespark: 1000000 - 100 - Group By Test Timespark: 10000000 - 500 - SHA-512 Benchmark Timespark: 1000000 - 500 - SHA-512 Benchmark Timespark: 1000000 - 500 - Inner Join Test Timespark: 10000000 - 500 - Broadcast Inner Join Test Timespark: 20000000 - 1000 - Inner Join Test Timespark: 20000000 - 500 - Inner Join Test Timespark: 20000000 - 2000 - Repartition Test Timespark: 1000000 - 500 - Group By Test Timespark: 20000000 - 2000 - Broadcast Inner Join Test Timespark: 40000000 - 2000 - SHA-512 Benchmark Timespark: 10000000 - 1000 - Group By Test Timespark: 1000000 - 500 - Broadcast Inner Join Test Timespark: 1000000 - 100 - SHA-512 Benchmark Timespark: 20000000 - 100 - Broadcast Inner Join Test Timespark: 10000000 - 2000 - Inner Join Test Timespark: 20000000 - 100 - Inner Join Test Timespark: 10000000 - 2000 - Group By Test Timespark: 10000000 - 500 - Inner Join Test Timespark: 20000000 - 100 - SHA-512 Benchmark Timespark: 1000000 - 2000 - SHA-512 Benchmark Timespark: 40000000 - 2000 - Inner Join Test Timespark: 20000000 - 100 - Group By Test Timespark: 10000000 - 100 - Inner Join Test Timespark: 20000000 - 2000 - Group By Test Timespark: 20000000 - 1000 - SHA-512 Benchmark Timespark: 20000000 - 1000 - Calculate Pi Benchmark Using Dataframespark: 20000000 - 500 - Repartition Test Timeai-benchmark: Device Inference Scorespark: 10000000 - 100 - Repartition Test Timespark: 40000000 - 100 - SHA-512 Benchmark Timespark: 10000000 - 2000 - Repartition Test Timespark: 40000000 - 1000 - SHA-512 Benchmark Timesvt-av1: Preset 10 - Bosphorus 4Kspark: 10000000 - 100 - Group By Test Timespark: 40000000 - 500 - Broadcast Inner Join Test Timelammps: Rhodopsin Proteinsvt-av1: Preset 8 - Bosphorus 4Kspark: 1000000 - 1000 - Group By Test Timespark: 40000000 - 100 - Inner Join Test Timespark: 10000000 - 500 - Repartition Test Timespark: 40000000 - 100 - Broadcast Inner Join Test Timespark: 20000000 - 1000 - Group By Test Timespark: 40000000 - 2000 - Group By Test Timeai-benchmark: Device AI Scorespark: 20000000 - 2000 - SHA-512 Benchmark Timespark: 10000000 - 1000 - Repartition Test Timespark: 1000000 - 500 - Calculate Pi Benchmarkspark: 20000000 - 500 - Calculate Pi Benchmarkspark: 40000000 - 500 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 2000 - Group By Test Timesvt-av1: Preset 10 - Bosphorus 1080pspark: 20000000 - 500 - Broadcast Inner Join Test Timespark: 40000000 - 500 - Inner Join Test Timespark: 1000000 - 500 - Repartition Test Timesvt-av1: Preset 4 - Bosphorus 1080pspark: 40000000 - 1000 - Broadcast Inner Join Test Timespark: 1000000 - 1000 - Repartition Test Timespark: 1000000 - 1000 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 1000 - Calculate Pi Benchmarkspark: 10000000 - 500 - Group By Test Timespark: 1000000 - 500 - Calculate Pi Benchmark Using Dataframespark: 40000000 - 2000 - Calculate Pi Benchmarkspark: 20000000 - 2000 - Calculate Pi Benchmark Using Dataframesvt-av1: Preset 8 - Bosphorus 1080pspark: 40000000 - 100 - Group By Test Timespark: 40000000 - 1000 - Repartition Test Timespark: 10000000 - 2000 - SHA-512 Benchmark Timespark: 20000000 - 500 - Group By Test Timespark: 40000000 - 2000 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 100 - Calculate Pi Benchmark Using Dataframespark: 40000000 - 100 - Calculate Pi Benchmark Using Dataframesvt-av1: Preset 12 - Bosphorus 1080pspark: 10000000 - 1000 - Broadcast Inner Join Test Timespark: 10000000 - 1000 - Calculate Pi Benchmarkspark: 10000000 - 500 - Calculate Pi Benchmarkspark: 20000000 - 100 - Calculate Pi Benchmark Using Dataframespark: 10000000 - 1000 - Calculate Pi Benchmark Using Dataframenode-web-tooling: spark: 40000000 - 100 - Repartition Test Timespark: 40000000 - 100 - Calculate Pi Benchmarkspark: 20000000 - 100 - Repartition Test Timeai-benchmark: Device Training Scorespark: 10000000 - 100 - Calculate Pi Benchmarkspark: 1000000 - 1000 - Broadcast Inner Join Test Timespark: 40000000 - 1000 - Calculate Pi Benchmark Using Dataframespark: 10000000 - 100 - Calculate Pi Benchmark Using Dataframespark: 40000000 - 1000 - Group By Test Timeinkscape: SVG Files To PNGspark: 40000000 - 1000 - Calculate Pi Benchmarkspark: 20000000 - 500 - SHA-512 Benchmark Timespark: 20000000 - 1000 - Repartition Test Timespark: 40000000 - 500 - Repartition Test Timespark: 20000000 - 1000 - Calculate Pi Benchmarklammps: 20k Atomsspark: 10000000 - 2000 - Calculate Pi Benchmarkspark: 40000000 - 2000 - Repartition Test Timespark: 40000000 - 500 - Calculate Pi Benchmarkprimesieve: 1e12spark: 10000000 - 500 - Calculate Pi Benchmark Using Dataframespark: 20000000 - 500 - Calculate Pi Benchmark Using Dataframesvt-av1: Preset 4 - Bosphorus 4Kspark: 10000000 - 100 - SHA-512 Benchmark Timespark: 20000000 - 100 - Calculate Pi Benchmarkspark: 1000000 - 100 - Calculate Pi Benchmarkastcenc: Fastspark: 40000000 - 500 - Group By Test Timeastcenc: Exhaustivespark: 20000000 - 2000 - Calculate Pi Benchmarkspark: 40000000 - 2000 - Broadcast Inner Join Test Timespark: 10000000 - 2000 - Calculate Pi Benchmark Using Dataframeprimesieve: 1e13astcenc: Thoroughspark: 1000000 - 2000 - Calculate Pi Benchmarkastcenc: Mediumspark: 1000000 - 2000 - Calculate Pi Benchmark Using Dataframeaircrack-ng: spark: 1000000 - 100 - Broadcast Inner Join Test TimeABCD1.691.981.903.502.4911.1243.7321.3211.77097561422.8011.371.91119.52215.902.4658.203.4115.863.321.7310.7321.7722.5720.143.4021.8860.616.861.433.3122.50335484211.8923.4084297977.2911.28705635230.563.7044.3810.5011.89578755810.3229.775.0520.00141210.22534233060.7710.4858.3889.6216.8443.3012.57652.0253.3745.1710.0144.44464178610.1622.85255230.4110.2885.1485.635.063.86305.70921.6943.661.907.09342.822.005.0685.616.405.0685.085.07142.24230.2438.8216.349.715.065.055.05446.74610.9985.9185.615.065.0514.6241.0986.1820.61114085.571.685.065.0726.7917.49485.5029.7619.5439.8485.5012.64785.2039.3985.5610.6255.055.062.43316.20796166385.1885.020832690285.181028.571.275185.7743.675.03134.35812.103785.3598.42765.0372757.4891.501.562.121.893.312.4411.9042.5320.4311.1422.0111.141.79117.60916.172.4256.463.4016.603.311.7310.9921.1022.1419.873.4022.1259.116.751.483.2823.6012.1923.797.0611.22092855930.423.7745.4410.1911.7010.2530.535.2519.75137710.4561.5710.47603994857.0488.1756.7843.5812.35751.5383.4645.9956508519.9244.5310.0022.77250531.2010.1486.6084.915.103.90303.4521.6843.451.877.08742.522.025.0186.366.395.1185.775.07143.35730.28529393938.22999812616.249.835.015.095.10443.17311.15443213386.0386.115.075.0914.7440.89306870185.77915979920.77112884.9227103391.665.055.0627.01380699417.69886.31482977329.7519.6639.7185.4412.5885.7839.0385.7610.5685.095.102.41416.1985.5585.094623072284.771528.641.278285.6643.405.05133.79212.105385.51091516698.52455.031.601.451.961.743.632.5310.9845.9020.8012.0023.5611.261.88112.77816.912.4056.373.4115.943.451.73203762711.3421.1021.4020.933.3822.8157.656.601.413.4122.8811.7324.117.2711.4531.693.7343.7310.1311.9810.4729.375.0519.44136110.5959.3910.3556.39366685388.0796.7043.6112.60550.4773.47285985744.6410.2245.1610.2722.55248730.4110.0585.8387.045.113.95300.67421.2244.391.917.20643.381.995.1184.7403882756.515.0286.415.03140.84830.3838.1916.519.755.095.015.02441.56711.1686.1585.935.005.0214.6940.5785.1020.87112685.951.675.045.0126.7017.57885.7629.7919.4540.0784.9812.6985.3039.0685.0510.6285.055.062.42816.1985.8011494684.62286.207828.511.283785.2443.575.02134.04812.148185.2698.65425.0472788.0231.471.672.231.913.502.3311.3644.4422.0111.2023.2811.891.88112.20615.962.5559.743.6015.683.261.8311.1722.2722.2920.753.2321.6758.066.931.413.2523.0012.2823.047.3811.7230.3498602243.8643.5710.5612.19061515710.0629.345.0620.18138310.2159.42445850410.7256.9786.7446.9242.2812.73651.0173.3845.7710.0245.6810.0323.14251731.1710.31018176887.3385.914.993.90298.74621.66585957243.961.877.06142.852.035.1085.286.505.0984.895.12141.94230.7738.1616.259.675.045.075.08439.84111.1284.89686478284.905.075.0914.5540.9385.3620.72113485.491.675.005.0326.8117.6485.3629.4719.5339.6585.8512.56385.9937770139.1585.3910.6525.065.082.4216.0985.7584.48284.202228.711.282685.2043.455.03134.2612.153985.2098.58375.0372751.251.50OpenBenchmarking.org

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Inner Join Test TimeABCD0.38030.76061.14091.52121.9015SE +/- 0.02, N = 31.691.561.451.67

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test TimeABCD0.50181.00361.50542.00722.509SE +/- 0.03, N = 111.982.121.962.23

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Repartition Test TimeABCD0.42980.85961.28941.71922.149SE +/- 0.00, N = 31.901.891.741.91

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark TimeABCD0.81681.63362.45043.26724.084SE +/- 0.01, N = 33.503.313.633.50

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Inner Join Test TimeABCD0.56931.13861.70792.27722.8465SE +/- 0.02, N = 112.492.442.532.33

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Broadcast Inner Join Test TimeABCD3691215SE +/- 0.03, N = 311.1211.9010.9811.36

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - Inner Join Test TimeABCD1020304050SE +/- 0.38, N = 943.7342.5345.9044.44

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - Broadcast Inner Join Test TimeABCD510152025SE +/- 0.13, N = 921.3220.4320.8022.01

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Broadcast Inner Join Test TimeABCD3691215SE +/- 0.09, N = 311.7711.1412.0011.20

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - Inner Join Test TimeABCD612182430SE +/- 0.15, N = 1222.8022.0123.5623.28

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Inner Join Test TimeABCD3691215SE +/- 0.30, N = 311.3711.1411.2611.89

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Inner Join Test TimeABCD0.42980.85961.28941.71922.149SE +/- 0.04, N = 31.911.791.881.88

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 12 - Input: Bosphorus 4KABCD306090120150SE +/- 0.12, N = 3119.52117.61112.78112.211. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - SHA-512 Benchmark TimeABCD48121620SE +/- 0.02, N = 315.9016.1716.9115.96

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Repartition Test TimeABCD0.57381.14761.72142.29522.869SE +/- 0.02, N = 112.462.422.402.55

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - SHA-512 Benchmark TimeABCD1326395265SE +/- 0.57, N = 958.2056.4656.3759.74

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Group By Test TimeABCD0.811.622.433.244.05SE +/- 0.02, N = 33.413.403.413.60

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - SHA-512 Benchmark TimeABCD48121620SE +/- 0.07, N = 315.8616.6015.9415.68

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark TimeABCD0.77631.55262.32893.10523.8815SE +/- 0.01, N = 33.323.313.453.26

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Inner Join Test TimeABCD0.41180.82361.23541.64722.059SE +/- 0.055733465, N = 31.7300000001.7300000001.7320376271.830000000

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Broadcast Inner Join Test TimeABCD3691215SE +/- 0.17, N = 310.7310.9911.3411.17

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - Inner Join Test TimeABCD510152025SE +/- 0.14, N = 921.7721.1021.1022.27

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - Inner Join Test TimeABCD510152025SE +/- 0.14, N = 322.5722.1421.4022.29

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - Repartition Test TimeABCD510152025SE +/- 0.08, N = 1220.1419.8720.9320.75

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Group By Test TimeABCD0.7651.532.2953.063.825SE +/- 0.02, N = 33.403.403.383.23

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - Broadcast Inner Join Test TimeABCD510152025SE +/- 0.15, N = 1221.8822.1222.8121.67

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - SHA-512 Benchmark TimeABCD1428425670SE +/- 0.37, N = 360.6159.1157.6558.06

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Group By Test TimeABCD246810SE +/- 0.03, N = 36.866.756.606.93

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test TimeABCD0.3330.6660.9991.3321.665SE +/- 0.04, N = 31.431.481.411.41

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark TimeABCD0.76731.53462.30193.06923.8365SE +/- 0.03, N = 33.313.283.413.25

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - Broadcast Inner Join Test TimeABCD612182430SE +/- 0.13, N = 322.5023.6022.8823.00

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Inner Join Test TimeABCD3691215SE +/- 0.04, N = 311.8912.1911.7312.28

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - Inner Join Test TimeABCD612182430SE +/- 0.43, N = 323.4123.7924.1123.04

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Group By Test TimeABCD246810SE +/- 0.08, N = 37.297.067.277.38

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Inner Join Test TimeABCD3691215SE +/- 0.08, N = 311.2911.2211.4511.72

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - SHA-512 Benchmark TimeABCD714212835SE +/- 0.27, N = 330.5630.4231.6930.35

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark TimeABCD0.86851.7372.60553.4744.3425SE +/- 0.03, N = 113.703.773.733.86

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - Inner Join Test TimeABCD1020304050SE +/- 0.17, N = 344.3845.4443.7343.57

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - Group By Test TimeABCD3691215SE +/- 0.11, N = 310.5010.1910.1310.56

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Inner Join Test TimeABCD3691215SE +/- 0.24, N = 311.9011.7011.9812.19

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - Group By Test TimeABCD3691215SE +/- 0.04, N = 1210.3210.2510.4710.06

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - SHA-512 Benchmark TimeABCD714212835SE +/- 0.25, N = 929.7730.5329.3729.34

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - Calculate Pi Benchmark Using DataframeABCD1.18132.36263.54394.72525.9065SE +/- 0.02, N = 95.055.255.055.06

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - Repartition Test TimeABCD510152025SE +/- 0.04, N = 320.0019.7519.4420.18

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Inference ScoreABCD300600900120015001412137713611383

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Repartition Test TimeABCD3691215SE +/- 0.04, N = 310.2310.4510.5910.21

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - SHA-512 Benchmark TimeABCD1428425670SE +/- 0.76, N = 360.7761.5759.3959.42

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Repartition Test TimeABCD3691215SE +/- 0.08, N = 310.4810.4810.3510.72

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - SHA-512 Benchmark TimeABCD1326395265SE +/- 0.48, N = 958.3857.0456.3956.97

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 10 - Input: Bosphorus 4KABCD20406080100SE +/- 0.57, N = 389.6288.1888.0886.741. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Group By Test TimeABCD246810SE +/- 0.05, N = 36.846.786.706.92

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - Broadcast Inner Join Test TimeABCD1020304050SE +/- 0.11, N = 943.3043.5843.6142.28

LAMMPS Molecular Dynamics Simulator

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 23Jun2022Model: Rhodopsin ProteinABCD3691215SE +/- 0.13, N = 512.5812.3612.6112.741. (CXX) g++ options: -O3 -lm -ldl

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 8 - Input: Bosphorus 4KABCD1224364860SE +/- 0.05, N = 352.0351.5450.4851.021. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Group By Test TimeABCD0.78141.56282.34423.12563.907SE +/- 0.017120473, N = 33.3700000003.4600000003.4728598573.380000000

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - Inner Join Test TimeABCD1020304050SE +/- 0.21, N = 345.1746.0044.6445.77

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Repartition Test TimeABCD3691215SE +/- 0.10, N = 310.019.9210.2210.02

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - Broadcast Inner Join Test TimeABCD1020304050SE +/- 0.23, N = 344.4444.5345.1645.68

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - Group By Test TimeABCD3691215SE +/- 0.05, N = 910.1610.0010.2710.03

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - Group By Test TimeABCD612182430SE +/- 0.18, N = 322.8522.7722.5523.14

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device AI ScoreABCD50010001500200025002552250524872517

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - SHA-512 Benchmark TimeABCD714212835SE +/- 0.24, N = 1230.4131.2030.4131.17

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Repartition Test TimeABCD3691215SE +/- 0.08, N = 310.2810.1410.0510.31

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.23, N = 385.1486.6085.8387.33

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.15, N = 385.6384.9187.0485.91

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark Using DataframeABCD1.14982.29963.44944.59925.749SE +/- 0.02, N = 95.065.105.114.99

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Group By Test TimeABCD0.88881.77762.66643.55524.444SE +/- 0.02, N = 113.863.903.953.90

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 10 - Input: Bosphorus 1080pABCD70140210280350SE +/- 0.90, N = 3305.71303.45300.67298.751. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - Broadcast Inner Join Test TimeABCD510152025SE +/- 0.20, N = 321.6921.6821.2221.67

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - Inner Join Test TimeABCD1020304050SE +/- 0.22, N = 943.6643.4544.3943.96

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Repartition Test TimeABCD0.42980.85961.28941.71922.149SE +/- 0.01, N = 31.901.871.911.87

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 4 - Input: Bosphorus 1080pABCD246810SE +/- 0.061, N = 37.0937.0877.2067.0611. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - Broadcast Inner Join Test TimeABCD1020304050SE +/- 0.16, N = 942.8242.5243.3842.85

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Repartition Test TimeABCD0.45680.91361.37041.82722.284SE +/- 0.02, N = 32.002.021.992.03

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using DataframeABCD1.14982.29963.44944.59925.749SE +/- 0.04, N = 35.065.015.115.10

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.81, N = 385.6186.3684.7485.28

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Group By Test TimeABCD246810SE +/- 0.02, N = 36.406.396.516.50

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using DataframeABCD1.14982.29963.44944.59925.749SE +/- 0.05, N = 35.065.115.025.09

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.13, N = 385.0885.7786.4184.89

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - Calculate Pi Benchmark Using DataframeABCD1.1522.3043.4564.6085.76SE +/- 0.02, N = 125.075.075.035.12

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 8 - Input: Bosphorus 1080pABCD306090120150SE +/- 0.73, N = 3142.24143.36140.85141.941. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - Group By Test TimeABCD714212835SE +/- 0.11, N = 330.2430.2930.3830.77

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - Repartition Test TimeABCD918273645SE +/- 0.15, N = 938.8238.2338.1938.16

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - SHA-512 Benchmark TimeABCD48121620SE +/- 0.06, N = 316.3416.2416.5116.25

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - Group By Test TimeABCD3691215SE +/- 0.08, N = 39.719.839.759.67

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - Calculate Pi Benchmark Using DataframeABCD1.14532.29063.43594.58125.7265SE +/- 0.03, N = 35.065.015.095.04

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using DataframeABCD1.14532.29063.43594.58125.7265SE +/- 0.01, N = 35.055.095.015.07

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - Calculate Pi Benchmark Using DataframeABCD1.14752.2953.44254.595.7375SE +/- 0.03, N = 35.055.105.025.08

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 12 - Input: Bosphorus 1080pABCD100200300400500SE +/- 3.06, N = 3446.75443.17441.57439.841. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Broadcast Inner Join Test TimeABCD3691215SE +/- 0.04, N = 310.9911.1511.1611.12

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.38, N = 385.9186.0386.1584.90

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.32, N = 385.6186.1185.9384.90

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - Calculate Pi Benchmark Using DataframeABCD1.14082.28163.42244.56325.704SE +/- 0.01, N = 35.065.075.005.07

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Using DataframeABCD1.14532.29063.43594.58125.7265SE +/- 0.01, N = 35.055.095.025.09

Node.js V8 Web Tooling Benchmark

Running the V8 project's Web-Tooling-Benchmark under Node.js. The Web-Tooling-Benchmark stresses JavaScript-related workloads common to web developers like Babel and TypeScript and Babylon. This test profile can test the system's JavaScript performance with Node.js. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgruns/s, More Is BetterNode.js V8 Web Tooling BenchmarkABCD48121620SE +/- 0.06, N = 314.6214.7414.6914.55

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - Repartition Test TimeABCD918273645SE +/- 0.12, N = 341.0940.8940.5740.93

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 100 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.98, N = 386.1885.7885.1085.36

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - Repartition Test TimeABCD510152025SE +/- 0.05, N = 320.6120.7720.8720.72

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Training ScoreABCD20040060080010001140112811261134

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.26, N = 385.5784.9285.9585.49

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test TimeABCD0.3780.7561.1341.5121.89SE +/- 0.05, N = 31.681.661.671.67

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - Calculate Pi Benchmark Using DataframeABCD1.13852.2773.41554.5545.6925SE +/- 0.01, N = 95.065.055.045.00

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Using DataframeABCD1.14082.28163.42244.56325.704SE +/- 0.01, N = 35.075.065.015.03

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - Group By Test TimeABCD612182430SE +/- 0.07, N = 926.7927.0126.7026.81

Inkscape

Inkscape is an open-source vector graphics editor. This test profile times how long it takes to complete various operations by Inkscape. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterInkscapeOperation: SVG Files To PNGABCD48121620SE +/- 0.14, N = 1217.4917.7017.5817.641. Inkscape 1.1.2 (0a00cf5339, 2022-02-04)

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 1000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.14, N = 985.5086.3185.7685.36

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - SHA-512 Benchmark TimeABCD714212835SE +/- 0.06, N = 329.7629.7529.7929.47

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - Repartition Test TimeABCD510152025SE +/- 0.04, N = 919.5419.6619.4519.53

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - Repartition Test TimeABCD918273645SE +/- 0.17, N = 939.8439.7140.0739.65

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 1000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.17, N = 985.5085.4484.9885.85

LAMMPS Molecular Dynamics Simulator

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 23Jun2022Model: 20k AtomsABCD3691215SE +/- 0.04, N = 312.6512.5812.6912.561. (CXX) g++ options: -O3 -lm -ldl

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.24, N = 385.2085.7885.3085.99

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - Repartition Test TimeABCD918273645SE +/- 0.30, N = 339.3939.0339.0639.15

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.16, N = 985.5685.7685.0585.39

Primesieve

Primesieve generates prime numbers using a highly optimized sieve of Eratosthenes implementation. Primesieve primarily benchmarks the CPU's L1/L2 cache performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPrimesieve 8.0Length: 1e12ABCD3691215SE +/- 0.01, N = 310.6310.5710.6310.651. (CXX) g++ options: -O3

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Using DataframeABCD1.14532.29063.43594.58125.7265SE +/- 0.01, N = 35.055.095.055.06

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 500 - Calculate Pi Benchmark Using DataframeABCD1.14752.2953.44254.595.7375SE +/- 0.01, N = 35.065.105.065.08

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.2Encoder Mode: Preset 4 - Input: Bosphorus 4KABCD0.54741.09481.64222.18962.737SE +/- 0.005, N = 32.4332.4142.4282.4201. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - SHA-512 Benchmark TimeABCD48121620SE +/- 0.01, N = 316.2116.1916.1916.09

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 100 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.06, N = 385.1885.5585.8085.75

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.27, N = 385.0285.0984.6284.48

ASTC Encoder

ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMT/s, More Is BetterASTC Encoder 4.0Preset: FastABCD60120180240300SE +/- 0.55, N = 3285.18284.77286.21284.201. (CXX) g++ options: -O3 -flto -pthread

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 500 - Group By Test TimeABCD714212835SE +/- 0.05, N = 928.5728.6428.5128.71

ASTC Encoder

ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMT/s, More Is BetterASTC Encoder 4.0Preset: ExhaustiveABCD0.28880.57760.86641.15521.444SE +/- 0.0020, N = 31.27511.27821.28371.28261. (CXX) g++ options: -O3 -flto -pthread

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 20000000 - Partitions: 2000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.19, N = 1285.7785.6685.2485.20

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 40000000 - Partitions: 2000 - Broadcast Inner Join Test TimeABCD1020304050SE +/- 0.38, N = 343.6743.4043.5743.45

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Using DataframeABCD1.13632.27263.40894.54525.6815SE +/- 0.02, N = 35.035.055.025.03

Primesieve

Primesieve generates prime numbers using a highly optimized sieve of Eratosthenes implementation. Primesieve primarily benchmarks the CPU's L1/L2 cache performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPrimesieve 8.0Length: 1e13ABCD306090120150SE +/- 0.15, N = 3134.36133.79134.05134.261. (CXX) g++ options: -O3

ASTC Encoder

ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMT/s, More Is BetterASTC Encoder 4.0Preset: ThoroughABCD3691215SE +/- 0.02, N = 312.1012.1112.1512.151. (CXX) g++ options: -O3 -flto -pthread

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Calculate Pi BenchmarkABCD20406080100SE +/- 0.18, N = 1185.3585.5185.2685.20

ASTC Encoder

ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMT/s, More Is BetterASTC Encoder 4.0Preset: MediumABCD20406080100SE +/- 0.03, N = 398.4398.5298.6598.581. (CXX) g++ options: -O3 -flto -pthread

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using DataframeABCD1.1342.2683.4024.5365.67SE +/- 0.01, N = 115.035.035.045.03

Aircrack-ng

Aircrack-ng is a tool for assessing WiFi/WLAN network security. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgk/s, More Is BetterAircrack-ng 1.7ACD16K32K48K64K80KSE +/- 123.96, N = 372757.4972788.0272751.251. (CXX) g++ options: -std=gnu++17 -O3 -fvisibility=hidden -fcommon -rdynamic -lnl-3 -lnl-genl-3 -lpcre -lpthread -lz -lssl -lcrypto -lhwloc -ldl -lm -pthread

B: The test run did not produce a result.

Apache Spark

This is a benchmark of Apache Spark with its PySpark interface. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmars the Apache Spark in a single-system configuration using spark-submit. The test makes use of DIYBigData's pyspark-benchmark (https://github.com/DIYBigData/pyspark-benchmark/) for generating of test data and various Apache Spark operations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test TimeABCD0.360.721.081.441.8SE +/- 0.11, N = 31.501.601.471.50

134 Results Shown

Apache Spark:
  1000000 - 100 - Inner Join Test Time
  1000000 - 2000 - Broadcast Inner Join Test Time
  1000000 - 100 - Repartition Test Time
  1000000 - 1000 - SHA-512 Benchmark Time
  1000000 - 2000 - Inner Join Test Time
  10000000 - 2000 - Broadcast Inner Join Test Time
  40000000 - 1000 - Inner Join Test Time
  20000000 - 1000 - Broadcast Inner Join Test Time
  10000000 - 100 - Broadcast Inner Join Test Time
  20000000 - 2000 - Inner Join Test Time
  10000000 - 1000 - Inner Join Test Time
  1000000 - 1000 - Inner Join Test Time
SVT-AV1
Apache Spark:
  10000000 - 1000 - SHA-512 Benchmark Time
  1000000 - 2000 - Repartition Test Time
  40000000 - 500 - SHA-512 Benchmark Time
  1000000 - 100 - Group By Test Time
  10000000 - 500 - SHA-512 Benchmark Time
  1000000 - 500 - SHA-512 Benchmark Time
  1000000 - 500 - Inner Join Test Time
  10000000 - 500 - Broadcast Inner Join Test Time
  20000000 - 1000 - Inner Join Test Time
  20000000 - 500 - Inner Join Test Time
  20000000 - 2000 - Repartition Test Time
  1000000 - 500 - Group By Test Time
  20000000 - 2000 - Broadcast Inner Join Test Time
  40000000 - 2000 - SHA-512 Benchmark Time
  10000000 - 1000 - Group By Test Time
  1000000 - 500 - Broadcast Inner Join Test Time
  1000000 - 100 - SHA-512 Benchmark Time
  20000000 - 100 - Broadcast Inner Join Test Time
  10000000 - 2000 - Inner Join Test Time
  20000000 - 100 - Inner Join Test Time
  10000000 - 2000 - Group By Test Time
  10000000 - 500 - Inner Join Test Time
  20000000 - 100 - SHA-512 Benchmark Time
  1000000 - 2000 - SHA-512 Benchmark Time
  40000000 - 2000 - Inner Join Test Time
  20000000 - 100 - Group By Test Time
  10000000 - 100 - Inner Join Test Time
  20000000 - 2000 - Group By Test Time
  20000000 - 1000 - SHA-512 Benchmark Time
  20000000 - 1000 - Calculate Pi Benchmark Using Dataframe
  20000000 - 500 - Repartition Test Time
AI Benchmark Alpha
Apache Spark:
  10000000 - 100 - Repartition Test Time
  40000000 - 100 - SHA-512 Benchmark Time
  10000000 - 2000 - Repartition Test Time
  40000000 - 1000 - SHA-512 Benchmark Time
SVT-AV1
Apache Spark:
  10000000 - 100 - Group By Test Time
  40000000 - 500 - Broadcast Inner Join Test Time
LAMMPS Molecular Dynamics Simulator
SVT-AV1
Apache Spark:
  1000000 - 1000 - Group By Test Time
  40000000 - 100 - Inner Join Test Time
  10000000 - 500 - Repartition Test Time
  40000000 - 100 - Broadcast Inner Join Test Time
  20000000 - 1000 - Group By Test Time
  40000000 - 2000 - Group By Test Time
AI Benchmark Alpha
Apache Spark:
  20000000 - 2000 - SHA-512 Benchmark Time
  10000000 - 1000 - Repartition Test Time
  1000000 - 500 - Calculate Pi Benchmark
  20000000 - 500 - Calculate Pi Benchmark
  40000000 - 500 - Calculate Pi Benchmark Using Dataframe
  1000000 - 2000 - Group By Test Time
SVT-AV1
Apache Spark:
  20000000 - 500 - Broadcast Inner Join Test Time
  40000000 - 500 - Inner Join Test Time
  1000000 - 500 - Repartition Test Time
SVT-AV1
Apache Spark:
  40000000 - 1000 - Broadcast Inner Join Test Time
  1000000 - 1000 - Repartition Test Time
  1000000 - 1000 - Calculate Pi Benchmark Using Dataframe
  1000000 - 1000 - Calculate Pi Benchmark
  10000000 - 500 - Group By Test Time
  1000000 - 500 - Calculate Pi Benchmark Using Dataframe
  40000000 - 2000 - Calculate Pi Benchmark
  20000000 - 2000 - Calculate Pi Benchmark Using Dataframe
SVT-AV1
Apache Spark:
  40000000 - 100 - Group By Test Time
  40000000 - 1000 - Repartition Test Time
  10000000 - 2000 - SHA-512 Benchmark Time
  20000000 - 500 - Group By Test Time
  40000000 - 2000 - Calculate Pi Benchmark Using Dataframe
  1000000 - 100 - Calculate Pi Benchmark Using Dataframe
  40000000 - 100 - Calculate Pi Benchmark Using Dataframe
SVT-AV1
Apache Spark:
  10000000 - 1000 - Broadcast Inner Join Test Time
  10000000 - 1000 - Calculate Pi Benchmark
  10000000 - 500 - Calculate Pi Benchmark
  20000000 - 100 - Calculate Pi Benchmark Using Dataframe
  10000000 - 1000 - Calculate Pi Benchmark Using Dataframe
Node.js V8 Web Tooling Benchmark
Apache Spark:
  40000000 - 100 - Repartition Test Time
  40000000 - 100 - Calculate Pi Benchmark
  20000000 - 100 - Repartition Test Time
AI Benchmark Alpha
Apache Spark:
  10000000 - 100 - Calculate Pi Benchmark
  1000000 - 1000 - Broadcast Inner Join Test Time
  40000000 - 1000 - Calculate Pi Benchmark Using Dataframe
  10000000 - 100 - Calculate Pi Benchmark Using Dataframe
  40000000 - 1000 - Group By Test Time
Inkscape
Apache Spark:
  40000000 - 1000 - Calculate Pi Benchmark
  20000000 - 500 - SHA-512 Benchmark Time
  20000000 - 1000 - Repartition Test Time
  40000000 - 500 - Repartition Test Time
  20000000 - 1000 - Calculate Pi Benchmark
LAMMPS Molecular Dynamics Simulator
Apache Spark:
  10000000 - 2000 - Calculate Pi Benchmark
  40000000 - 2000 - Repartition Test Time
  40000000 - 500 - Calculate Pi Benchmark
Primesieve
Apache Spark:
  10000000 - 500 - Calculate Pi Benchmark Using Dataframe
  20000000 - 500 - Calculate Pi Benchmark Using Dataframe
SVT-AV1
Apache Spark:
  10000000 - 100 - SHA-512 Benchmark Time
  20000000 - 100 - Calculate Pi Benchmark
  1000000 - 100 - Calculate Pi Benchmark
ASTC Encoder
Apache Spark
ASTC Encoder
Apache Spark:
  20000000 - 2000 - Calculate Pi Benchmark
  40000000 - 2000 - Broadcast Inner Join Test Time
  10000000 - 2000 - Calculate Pi Benchmark Using Dataframe
Primesieve
ASTC Encoder
Apache Spark
ASTC Encoder
Apache Spark
Aircrack-ng
Apache Spark