Fedora 33 Benchmarks

Various open-source benchmarks by the Phoronix Test Suite v9.0.1 (Asker).

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2010168-AS-FEDORA33B97
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HPC - High Performance Computing 2 Tests
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2020-10-15 05:16
October 15 2020
  1 Hour, 35 Minutes
Intel Core i7-6820HQ
October 16 2020
  2 Minutes
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Fedora 33 BenchmarksOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-6820HQ @ 3.60GHz (4 Cores / 8 Threads)Dell Latitude E5470 (1.22.3 BIOS)Intel Xeon E3-1200 v5/E3-150032768MB1000GB Samsung SSD 840Intel HD 530 3GB (1050MHz)Realtek ALC3235Intel I219-LM + Intel 8260Fedora 335.8.14-300.fc33.x86_64 (x86_64)GNOME Shell 3.38.1X Server + Wayland4.6 Mesa 20.2.04.6 Mesa 20.2.1GCC 10.2.1 20201005btrfs1600x900ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLsCompilerFile-SystemScreen ResolutionFedora 33 Benchmarks PerformanceSystem Logs- --build=x86_64-redhat-linux --disable-libunwind-exceptions --enable-__cxa_atexit --enable-bootstrap --enable-cet --enable-checking=release --enable-gnu-indirect-function --enable-gnu-unique-object --enable-initfini-array --enable-languages=c,c++,fortran,objc,obj-c++,ada,go,d,lto --enable-multilib --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-arch_32=i686 --with-gcc-major-version-only --with-isl --with-linker-hash-style=gnu --with-tune=generic --without-cuda-driver - Scaling Governor: intel_pstate powersave- 2020-10-15 05:16: OpenJDK Runtime Environment 18.9 (build 11.0.9-ea+10) - 2020-10-15 05:16: Python 3.9.0- SELinux + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + 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 Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Vulnerable: No microcode + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

Fedora 33 Benchmarkstensorflow-lite: Mobilenet Floatbasis: ETC1Smnn: SqueezeNetV1.0mnn: resnet-v2-50mnn: MobileNetV2_224mnn: mobilenet-v1-1.0mnn: inception-v3mkl-dnn: Deconvolution Batch deconv_1d - f322020-10-15 05:16Intel Core i7-6820HQ482043122.0024.64113.5414.2618.66137.2114.24OpenBenchmarking.org

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet Float2020-10-15 05:16100K200K300K400K500KSE +/- 1224.74, N = 3482043

Basis Universal

Basis Universal is a GPU texture codoec. This test times how long it takes to convert sRGB PNGs into Basis Univeral assets with various settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBasis Universal 1.12Settings: ETC1S2020-10-15 05:16306090120150SE +/- 0.24, N = 3122.001. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O2 -rdynamic -lm -lpthread

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by ALibaba. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2020-09-17Model: SqueezeNetV1.02020-10-15 05:16612182430SE +/- 0.11, N = 324.64MIN: 15.83 / MAX: 85.311. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2020-09-17Model: resnet-v2-502020-10-15 05:16306090120150SE +/- 0.69, N = 3113.54MIN: 86.75 / MAX: 215.021. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2020-09-17Model: MobileNetV2_2242020-10-15 05:1648121620SE +/- 0.19, N = 314.26MIN: 7.32 / MAX: 85.51. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2020-09-17Model: mobilenet-v1-1.02020-10-15 05:16510152025SE +/- 0.13, N = 318.66MIN: 10.82 / MAX: 58.261. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2020-09-17Model: inception-v32020-10-15 05:16306090120150SE +/- 1.14, N = 3137.21MIN: 108.1 / MAX: 251.931. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

oneDNN MKL-DNN

This is a test of the Intel oneDNN (formerly DNNL / Deep Neural Network Library / MKL-DNN) as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Deconvolution Batch deconv_1d - Data Type: f32Intel Core i7-6820HQ48121620SE +/- 0.02, N = 314.24MIN: 13.381. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -O2 -pie -lpthread -lrt -ldl