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AMD Ryzen Z1 Extreme testing with a ASUS RC71L v1.0 (RC71L.319 BIOS) and ASUS AMD Phoenix1 4GB on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2401077-NE-FG801576407&sro&grs.

fgProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionanAMD Ryzen Z1 Extreme @ 5.29GHz (8 Cores / 16 Threads)ASUS RC71L v1.0 (RC71L.319 BIOS)AMD Device 14e812GB512GB Micron_2400_MTFDKBK512QFM + 1000GB RTL9210B-CGASUS AMD Phoenix1 4GB (2700/800MHz)AMD Rembrandt Radeon HD AudioMEDIATEK MT7922 802.11ax PCIUbuntu 23.106.7.0-060700rc5-generic (x86_64)GNOME Shell 45.1X Server + Wayland4.6 Mesa 24.0~git2401050600.91ec3c~oibaf~m (git-91ec3cc 2024-01-05 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.56)GCC 13.2.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --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,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-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/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 Processor Details- Scaling Governor: amd-pstate-epp powersave (EPP: performance) - Platform Profile: performance - CPU Microcode: 0xa704103 - ACPI Profile: performance Python Details- Python 3.11.6Security Details- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Vulnerable: Safe RET no microcode + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

fgpytorch: CPU - 16 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_ly-cruncher: 1Bquicksilver: CTS2tensorflow: CPU - 1 - VGG-16tensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 1 - GoogLeNettensorflow: CPU - 16 - VGG-16pytorch: CPU - 1 - ResNet-50tensorflow: CPU - 16 - AlexNettensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 1 - AlexNetpytorch: CPU - 16 - Efficientnet_v2_lquicksilver: CORAL2 P2quicksilver: CORAL2 P1y-cruncher: 500Mtensorflow: CPU - 16 - ResNet-50an12.2028.8119.5311.4537.197105500003.7467.7941.677.1347.2592.7612.1912.727.85204700001097000016.15822.6211.6728.1019.1011.3136.761104900003.7667.4641.477.147.0692.4912.1712.77.84204900001096000016.16722.61OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152an369121512.2011.67MIN: 11.76 / MAX: 12.59MIN: 11.31 / MAX: 12.32

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50an71421283528.8128.10MIN: 26.48 / MAX: 29.59MIN: 27.36 / MAX: 29.59

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152an51015202519.5319.10MIN: 19.2 / MAX: 19.87MIN: 18.01 / MAX: 19.53

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_lan369121511.4511.31MIN: 11.1 / MAX: 11.62MIN: 10.75 / MAX: 11.6

Y-Cruncher

Pi Digits To Calculate: 1B

OpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.3Pi Digits To Calculate: 1Ban91827364537.2036.76

Quicksilver

Input: CTS2

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CTS2an2M4M6M8M10M10550000104900001. (CXX) g++ options: -fopenmp -O3 -march=native

TensorFlow

Device: CPU - Batch Size: 1 - Model: VGG-16

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: VGG-16an0.8461.6922.5383.3844.233.743.76

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetan153045607567.7967.46

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: GoogLeNetan102030405041.6741.47

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: VGG-16an2468107.137.10

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50an112233445547.2547.06MIN: 39.95 / MAX: 47.92MIN: 43.44 / MAX: 47.88

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetan2040608010092.7692.49

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: ResNet-50an369121512.1912.17

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: AlexNetan369121512.7212.70

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_lan2468107.857.84MIN: 6.78 / MAX: 8.29MIN: 6.18 / MAX: 8.44

Quicksilver

Input: CORAL2 P2

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P2an4M8M12M16M20M20470000204900001. (CXX) g++ options: -fopenmp -O3 -march=native

Quicksilver

Input: CORAL2 P1

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P1an2M4M6M8M10M10970000109600001. (CXX) g++ options: -fopenmp -O3 -march=native

Y-Cruncher

Pi Digits To Calculate: 500M

OpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.3Pi Digits To Calculate: 500Man4812162016.1616.17

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50an51015202522.6222.61

Phoronix Test Suite v10.8.4