octty

Apple M2 testing with a Apple MacBook Air (13 h M2 2022) and llvmpipe on Arch rolling 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 2310243-NE-OCTTY849561
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October 24 2023
  51 Minutes
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October 24 2023
  53 Minutes
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October 24 2023
  53 Minutes
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octtyOpenBenchmarking.orgPhoronix Test SuiteApple M2 @ 2.42GHz (4 Cores / 8 Threads)Apple MacBook Air (13 h M2 2022)Apple Silicon8GB251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256ZllvmpipeBroadcom Device 4433 + Broadcom BRCM4387 BluetoothArch rolling6.3.0-asahi-13-1-ARCH (aarch64)KDE Plasma 5.27.6X Server 1.21.1.84.5 Mesa 23.1.3 (LLVM 15.0.7 128 bits)GCC 12.1.0 + Clang 15.0.7ext42560x1600ProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionOctty BenchmarksSystem Logs- --build=aarch64-unknown-linux-gnu --disable-libssp --disable-libstdcxx-pch --disable-multilib --disable-werror --enable-__cxa_atexit --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-default-ssp --enable-fix-cortex-a53-835769 --enable-fix-cortex-a53-843419 --enable-gnu-indirect-function --enable-gnu-unique-object --enable-languages=c,c++,fortran,go,lto,objc,obj-c++ --enable-lto --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-unknown-linux-gnu --mandir=/usr/share/man --with-arch=armv8-a --with-linker-hash-style=gnu - Scaling Governor: apple-cpufreq schedutil (Boost: Enabled)- a: OpenJDK Runtime Environment (build 11.0.19+7)- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Not affected + srbds: Not affected + tsx_async_abort: Not affected

QuantLib

QuantLib is an open-source library/framework around quantitative finance for modeling, trading and risk management scenarios. QuantLib is written in C++ with Boost and its built-in benchmark used reports the QuantLib Benchmark Index benchmark score. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMFLOPS, More Is BetterQuantLib 1.32Configuration: Multi-Threadedabc5K10K15K20K25K19836.621315.121018.91. (CXX) g++ options: -O3 -march=native -fPIE -pie

OpenBenchmarking.orgMFLOPS, More Is BetterQuantLib 1.32Configuration: Single-Threadedabc90018002700360045004360.54345.94385.11. (CXX) g++ options: -O3 -march=native -fPIE -pie

easyWave

The easyWave software allows simulating tsunami generation and propagation in the context of early warning systems. EasyWave supports making use of OpenMP for CPU multi-threading and there are also GPU ports available but not currently incorporated as part of this test profile. The easyWave tsunami generation software is run with one of the example/reference input files for measuring the CPU execution time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240abc2468107.5297.5847.5361. (CXX) g++ options: -O3 -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200abc306090120150137.05135.22134.361. (CXX) g++ options: -O3 -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400abc80160240320400382.86345.19343.331. (CXX) g++ options: -O3 -fopenmp

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: mobilenetabc369121510.2310.9010.61MIN: 7.97 / MAX: 12.05MIN: 7.96 / MAX: 21.38MIN: 7.96 / MAX: 23.381. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU-v2-v2 - Model: mobilenet-v2abc0.46130.92261.38391.84522.30652.042.052.05MIN: 2.02 / MAX: 2.53MIN: 2.03 / MAX: 2.4MIN: 2.02 / MAX: 2.431. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU-v3-v3 - Model: mobilenet-v3abc0.44550.8911.33651.7822.22751.981.901.89MIN: 1.86 / MAX: 4.08MIN: 1.88 / MAX: 2.11MIN: 1.87 / MAX: 2.281. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: shufflenet-v2abc0.360.721.081.441.81.591.601.58MIN: 1.56 / MAX: 1.88MIN: 1.58 / MAX: 1.9MIN: 1.56 / MAX: 1.911. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: efficientnet-b0abc0.81681.63362.45043.26724.0843.183.113.63MIN: 3.11 / MAX: 11.55MIN: 3.1 / MAX: 3.92MIN: 3.1 / MAX: 17.411. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: blazefaceabc0.18680.37360.56040.74720.9340.770.800.83MIN: 0.75 / MAX: 0.84MIN: 0.76 / MAX: 0.93MIN: 0.75 / MAX: 4.661. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: googlenetabc36912159.299.289.21MIN: 7.69 / MAX: 26.66MIN: 7.75 / MAX: 17.28MIN: 7.81 / MAX: 18.231. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: vgg16abc71421283527.5527.5427.88MIN: 26.14 / MAX: 35.33MIN: 26.14 / MAX: 37.31MIN: 26.2 / MAX: 45.221. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: resnet18abc1.27352.5473.82055.0946.36755.335.335.66MIN: 4.77 / MAX: 10.67MIN: 4.76 / MAX: 7.71MIN: 4.77 / MAX: 15.451. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: alexnetabc2468107.827.897.88MIN: 7.56 / MAX: 9.47MIN: 7.53 / MAX: 16.17MIN: 7.55 / MAX: 15.761. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: resnet50abc4812162013.6013.3513.72MIN: 12.46 / MAX: 20.46MIN: 12.45 / MAX: 21.52MIN: 12.45 / MAX: 22.111. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: yolov4-tinyabc369121512.6712.6312.88MIN: 11.47 / MAX: 15.76MIN: 11.49 / MAX: 15.24MIN: 11.45 / MAX: 16.551. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: squeezenet_ssdabc2468107.297.717.46MIN: 5.77 / MAX: 15.12MIN: 5.82 / MAX: 15.39MIN: 5.79 / MAX: 15.341. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: regnety_400mabc1.13632.27263.40894.54525.68155.055.004.94MIN: 4.98 / MAX: 16.63MIN: 4.99 / MAX: 5.04MIN: 4.89 / MAX: 8.11. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: vision_transformerabc60120180240300280.14281.38280.32MIN: 249.27 / MAX: 310.78MIN: 247.76 / MAX: 303.62MIN: 248.11 / MAX: 317.171. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: FastestDetabc0.38480.76961.15441.53921.9241.701.711.69MIN: 1.68 / MAX: 1.72MIN: 1.61 / MAX: 3.12MIN: 1.6 / MAX: 1.911. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.9Video Input: Bosphorus 4K - Video Preset: Fastabc0.44330.88661.32991.77322.21651.9701.6941.7101. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.9Video Input: Bosphorus 4K - Video Preset: Fasterabc0.85141.70282.55423.40564.2573.7843.4453.4501. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.9Video Input: Bosphorus 1080p - Video Preset: Fastabc2468106.2905.8685.8951. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.9Video Input: Bosphorus 1080p - Video Preset: Fasterabc4812162014.5414.0614.051. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: mnasnetbc0.450.91.351.82.252.001.98MIN: 1.97 / MAX: 2.52MIN: 1.96 / MAX: 2.381. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread