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&grs&sor.

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

dddpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 64 - ResNet-50pytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 1 - ResNet-152ffmpeg: libx264 - Platformpytorch: CPU - 32 - ResNet-50ffmpeg: libx265 - Livepytorch: CPU - 512 - Efficientnet_v2_lffmpeg: libx265 - Platformpytorch: CPU - 16 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-152ffmpeg: libx264 - Video On Demandffmpeg: libx265 - Video On Demandpytorch: CPU - 256 - ResNet-50pytorch: CPU - 1 - ResNet-50ffmpeg: libx264 - Liveffmpeg: libx264 - Uploadpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 512 - ResNet-50pytorch: CPU - 16 - ResNet-50ffmpeg: libx265 - Uploadjava-scimark2: Compositeab1.512.372.354.831.513.1454.544.8337.091.5120.622.272.332.3554.3620.574.796.31226.5013.921.511.510.574.764.7611.461.442.312.404.751.493.1154.084.7936.791.5020.732.282.342.3654.5120.524.806.32226.8313.941.511.510.574.764.7611.46OpenBenchmarking.org

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: 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-152ba0.541.081.622.162.72.402.35MIN: 1.95 / MAX: 2.52MIN: 1.89 / MAX: 2.52

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: 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: 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

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

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

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

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

FFmpeg

Encoder: libx265 - Scenario: Platform

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Platformba51015202520.7320.621. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ba0.5131.0261.5392.0522.5652.282.27MIN: 1.89 / MAX: 2.43MIN: 1.88 / MAX: 2.4

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ba0.52651.0531.57952.1062.63252.342.33MIN: 1.93 / MAX: 2.49MIN: 1.93 / MAX: 2.49

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152ba0.5311.0621.5932.1242.6552.362.35MIN: 0.97 / MAX: 2.47MIN: 1.95 / MAX: 2.53

FFmpeg

Encoder: libx264 - Scenario: Video On Demand

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Video On Demandba122436486054.5154.361. (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: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ba1.082.163.244.325.44.804.79MIN: 3.73 / MAX: 5.18MIN: 3.46 / MAX: 5.14

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ba2468106.326.31MIN: 4.74 / MAX: 6.81MIN: 4.99 / MAX: 6.8

FFmpeg

Encoder: libx264 - Scenario: Live

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Liveba50100150200250226.83226.501. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

FFmpeg

Encoder: libx264 - Scenario: Upload

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Uploadba4812162013.9413.921. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

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_lba0.33980.67961.01941.35921.6991.511.51MIN: 1.37 / MAX: 1.58MIN: 1.37 / MAX: 1.6

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_lba0.33980.67961.01941.35921.6991.511.51MIN: 1.35 / MAX: 1.6MIN: 1.37 / MAX: 1.59

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_lba0.12830.25660.38490.51320.64150.570.57MIN: 0.34 / MAX: 1.04MIN: 0.32 / MAX: 1.03

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50ba1.0712.1423.2134.2845.3554.764.76MIN: 3.77 / MAX: 5.11MIN: 3.66 / MAX: 5.19

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ba1.0712.1423.2134.2845.3554.764.76MIN: 3.76 / MAX: 5.1MIN: 3.56 / MAX: 5.13

FFmpeg

Encoder: libx265 - Scenario: Upload

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Uploadba369121511.4611.461. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl

Phoronix Test Suite v10.8.5