ddd

Tests for a future article. Apple M2 testing with a Apple MacBook Air (13 h M2 2022) and llvmpipe on Arch rolling via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2311232-NE-DDD00616700&grt.

dddProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionabApple 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 15.0.7ext42560x1600OpenBenchmarking.orgCompiler Details- --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 Processor Details- Scaling Governor: apple-cpufreq schedutil (Boost: Enabled)Java Details- OpenJDK Runtime Environment (build 11.0.19+7)Python Details- Python 3.11.3Security Details- 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

dddffmpeg: libx264 - Liveffmpeg: libx265 - Liveffmpeg: libx264 - Uploadffmpeg: libx265 - Uploadffmpeg: libx264 - Platformffmpeg: libx265 - Platformffmpeg: libx264 - Video On Demandffmpeg: libx265 - Video On Demandpytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lbuild-ffmpeg: Time To Compileab226.5037.0913.9211.4654.5420.6254.3620.576.313.144.764.834.832.274.792.334.762.372.352.350.571.511.511.511.511.51226.8336.7913.9411.4654.0820.7354.5120.526.323.114.764.794.752.284.802.344.762.312.402.360.571.511.511.441.491.50OpenBenchmarking.org

FFmpeg

Encoder: libx264 - Scenario: Live

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Liveab50100150200250226.50226.831. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx265 - Scenario: Live

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Liveab91827364537.0936.791. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx264 - Scenario: Upload

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Uploadab4812162013.9213.941. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx265 - Scenario: Upload

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Uploadab369121511.4611.461. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx264 - Scenario: Platform

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Platformab122436486054.5454.081. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx265 - Scenario: Platform

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Platformab51015202520.6220.731. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx264 - Scenario: Video On Demand

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Video On Demandab122436486054.3654.511. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx265 - Scenario: Video On Demand

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Video On Demandab51015202520.5720.521. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab2468106.316.32MIN: 4.99 / MAX: 6.8MIN: 4.74 / MAX: 6.81

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ab0.70651.4132.11952.8263.53253.143.11MIN: 2.41 / MAX: 3.55MIN: 2.43 / MAX: 3.51

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ab1.0712.1423.2134.2845.3554.764.76MIN: 3.56 / MAX: 5.13MIN: 3.76 / MAX: 5.1

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ab1.08682.17363.26044.34725.4344.834.79MIN: 3.68 / MAX: 5.21MIN: 3.7 / MAX: 5.14

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab1.08682.17363.26044.34725.4344.834.75MIN: 3.59 / MAX: 5.16MIN: 3.61 / MAX: 5.06

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ab0.5131.0261.5392.0522.5652.272.28MIN: 1.88 / MAX: 2.4MIN: 1.89 / MAX: 2.43

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ab1.082.163.244.325.44.794.80MIN: 3.46 / MAX: 5.14MIN: 3.73 / MAX: 5.18

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ab0.52651.0531.57952.1062.63252.332.34MIN: 1.93 / MAX: 2.49MIN: 1.93 / MAX: 2.49

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50ab1.0712.1423.2134.2845.3554.764.76MIN: 3.66 / MAX: 5.19MIN: 3.77 / MAX: 5.11

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152ab0.53331.06661.59992.13322.66652.372.31MIN: 1.92 / MAX: 2.49MIN: 1.86 / MAX: 2.48

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ab0.541.081.622.162.72.352.40MIN: 1.89 / MAX: 2.52MIN: 1.95 / MAX: 2.52

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152ab0.5311.0621.5932.1242.6552.352.36MIN: 1.95 / MAX: 2.53MIN: 0.97 / MAX: 2.47

PyTorch

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lab0.12830.25660.38490.51320.64150.570.57MIN: 0.32 / MAX: 1.03MIN: 0.34 / MAX: 1.04

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lab0.33980.67961.01941.35921.6991.511.51MIN: 1.37 / MAX: 1.59MIN: 1.35 / MAX: 1.6

PyTorch

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lab0.33980.67961.01941.35921.6991.511.51MIN: 1.37 / MAX: 1.6MIN: 1.37 / MAX: 1.58

PyTorch

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lab0.33980.67961.01941.35921.6991.511.44MIN: 1.38 / MAX: 1.59MIN: 1.31 / MAX: 1.51

PyTorch

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lab0.33980.67961.01941.35921.6991.511.49MIN: 1.35 / MAX: 1.59MIN: 1.34 / MAX: 1.57

PyTorch

Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lab0.33980.67961.01941.35921.6991.511.50MIN: 0.79 / MAX: 1.6MIN: 1.34 / MAX: 1.58

Phoronix Test Suite v10.8.5