fhd

AMD Ryzen 5 5500U testing with a NB01 NL5xNU (1.07.11RTR1 BIOS) and AMD Lucienne 512MB on Tuxedo 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2401075-NE-FHD99334640&rdt&grw.

fhdProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionsbcAMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads)NB01 NL5xNU (1.07.11RTR1 BIOS)AMD Renoir/Cezanne16GBSamsung SSD 970 EVO Plus 500GBAMD Lucienne 512MB (1800/400MHz)AMD Renoir Radeon HD AudioRealtek RTL8111/8168/8411 + Intel Wi-Fi 6 AX200Tuxedo 22.046.0.0-1010-oem (x86_64)KDE Plasma 5.26.5X Server 1.21.1.34.6 Mesa 22.3.7 (LLVM 14.0.0 DRM 3.48)1.3.230GCC 11.3.0ext41920x1080OpenBenchmarking.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,brig,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-targets=nvptx-none=/build/gcc-11-xKiWfi/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-xKiWfi/gcc-11-11.3.0/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 ondemand (Boost: Enabled) - CPU Microcode: 0x8608103 Python Details- Python 3.10.6Security Details- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

fhdtensorflow: CPU - 16 - ResNet-50quicksilver: CORAL2 P1tensorflow: CPU - 32 - ResNet-50quicksilver: CORAL2 P2tensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 64 - ResNet-50pytorch: 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 - 32 - ResNet-152quicksilver: CTS2pytorch: CPU - 64 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lsbc6.5560856676.66113866674.356.6718.087.349.889.9310.004.244.2458016674.214.882.962.983.016.4960900006.64113900004.286.6818.617.5710.1310.3810.104.354.2858150004.344.953.002.972.976.4760710006.63113700004.286.6817.687.4810.0510.1010.054.274.2257700004.334.923.003.013.04OpenBenchmarking.org

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50sbc246810SE +/- 0.00, N = 36.556.496.47

Quicksilver

Input: CORAL2 P1

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P1sbc1.3M2.6M3.9M5.2M6.5MSE +/- 13920.41, N = 36085667609000060710001. (CXX) g++ options: -fopenmp -O3 -march=native

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50sbc246810SE +/- 0.01, N = 36.666.646.63

Quicksilver

Input: CORAL2 P2

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P2sbc2M4M6M8M10MSE +/- 29059.33, N = 31138666711390000113700001. (CXX) g++ options: -fopenmp -O3 -march=native

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: ResNet-50sbc0.97881.95762.93643.91524.894SE +/- 0.00, N = 34.354.284.28

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50sbc246810SE +/- 0.01, N = 36.676.686.68

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50sbc510152025SE +/- 0.14, N = 318.0818.6117.68MIN: 15.84 / MAX: 21.76MIN: 16.39 / MAX: 21.61MIN: 12.28 / MAX: 21.23

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152sbc246810SE +/- 0.05, N = 37.347.577.48MIN: 4.67 / MAX: 9.47MIN: 4.43 / MAX: 9.03MIN: 4.76 / MAX: 9.16

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50sbc3691215SE +/- 0.06, N = 39.8810.1310.05MIN: 5.98 / MAX: 12.22MIN: 6.6 / MAX: 12.34MIN: 5.43 / MAX: 11.83

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50sbc3691215SE +/- 0.04, N = 39.9310.3810.10MIN: 6.31 / MAX: 12.54MIN: 7.09 / MAX: 12.44MIN: 6.02 / MAX: 12.08

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50sbc3691215SE +/- 0.11, N = 510.0010.1010.05MIN: 5.78 / MAX: 12.3MIN: 6.91 / MAX: 12.22MIN: 5.43 / MAX: 12.02

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152sbc0.97881.95762.93643.91524.894SE +/- 0.03, N = 34.244.354.27MIN: 2.77 / MAX: 5.36MIN: 2.67 / MAX: 5.28MIN: 2.71 / MAX: 5.35

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152sbc0.9631.9262.8893.8524.815SE +/- 0.00, N = 34.244.284.22MIN: 2.69 / MAX: 5.49MIN: 2.77 / MAX: 5.34MIN: 2.82 / MAX: 5.35

Quicksilver

Input: CTS2

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CTS2sbc1.2M2.4M3.6M4.8M6MSE +/- 13169.83, N = 35801667581500057700001. (CXX) g++ options: -fopenmp -O3 -march=native

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152sbc0.97651.9532.92953.9064.8825SE +/- 0.05, N = 34.214.344.33MIN: 2.71 / MAX: 5.3MIN: 2.83 / MAX: 5.5MIN: 2.76 / MAX: 5.39

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_lsbc1.11382.22763.34144.45525.569SE +/- 0.03, N = 34.884.954.92MIN: 3.43 / MAX: 5.79MIN: 4.2 / MAX: 5.61MIN: 4.35 / MAX: 5.62

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_lsbc0.6751.352.0252.73.375SE +/- 0.03, N = 32.963.003.00MIN: 2 / MAX: 3.69MIN: 2.07 / MAX: 3.61MIN: 2.06 / MAX: 3.49

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_lsbc0.67731.35462.03192.70923.3865SE +/- 0.01, N = 32.982.973.01MIN: 1.88 / MAX: 3.59MIN: 2.06 / MAX: 3.53MIN: 2.1 / MAX: 3.55

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_lsbc0.6841.3682.0522.7363.42SE +/- 0.00, N = 33.012.973.04MIN: 2 / MAX: 3.67MIN: 2 / MAX: 3.54MIN: 2 / MAX: 3.59

Phoronix Test Suite v10.8.4