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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2401075-NE-FHD99334640
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fhd - Phoronix Test Suite

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&grr&rdt.

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 - 64 - ResNet-50quicksilver: CTS2pytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_ltensorflow: CPU - 32 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 64 - ResNet-152quicksilver: CORAL2 P2tensorflow: CPU - 16 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 1 - Efficientnet_v2_lquicksilver: CORAL2 P1pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 1 - ResNet-50tensorflow: CPU - 1 - ResNet-50sbc6.6758016672.962.983.016.664.244.244.21113866676.5510.004.8860856679.889.937.3418.084.356.6858150003.002.972.976.644.354.284.34113900006.4910.104.95609000010.1310.387.5718.614.286.6857700003.003.013.046.634.274.224.33113700006.4710.054.92607100010.0510.107.4817.684.28OpenBenchmarking.org

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

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: 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

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

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

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

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: 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

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: 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

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

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: 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: 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

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

Phoronix Test Suite v10.8.4