tests

AMD Ryzen 5 5500U testing with a NB01 TUXEDO Aura 15 Gen2 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/2403275-NE-TESTS110635&sor&grs.

testsProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionabAMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads)NB01 TUXEDO Aura 15 Gen2 NL5xNU (1.07.11RTR1 BIOS)AMD Renoir/Cezanne2 x 8GB DDR4-3200MT/s Samsung M471A1K43DB1-CWESamsung SSD 970 EVO Plus 500GBAMD Lucienne 512MB (1800/1333MHz)AMD Renoir Radeon HD AudioRealtek RTL8111/8168/8211/8411 + Intel Wi-Fi 6 AX200Tuxedo 22.046.5.0-10027-tuxedo (x86_64)KDE Plasma 5.27.10X Server 1.21.1.44.6 Mesa 24.0.3-0tux2 (LLVM 15.0.7 DRM 3.54)1.3.274GCC 11.4.0ext41920x1080OpenBenchmarking.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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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: balance_performance) - CPU Microcode: 0x8608103 Python Details- Python 3.10.12Security 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: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of Safe RET + 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

testspytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lblender: Pabellon Barcelona - CPU-Onlytensorflow: CPU - 32 - VGG-16pytorch: CPU - 512 - ResNet-152pytorch: CPU - 16 - Efficientnet_v2_lblender: Barbershop - CPU-Onlypytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lbuild-mesa: Time To Compilepytorch: CPU - 512 - Efficientnet_v2_lpytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-50blender: Fishy Cat - CPU-Onlytensorflow: CPU - 16 - VGG-16pytorch: CPU - 16 - ResNet-152pytorch: CPU - 1 - ResNet-152tensorflow: CPU - 32 - GoogLeNetblender: Classroom - CPU-Onlytensorflow: CPU - 16 - GoogLeNetpytorch: CPU - 1 - ResNet-50tensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50tensorflow: CPU - 32 - AlexNetpytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-152tensorflow: CPU - 16 - AlexNettensorflow: CPU - 1 - AlexNetpytorch: CPU - 64 - ResNet-152tensorflow: CPU - 1 - VGG-16blender: BMW27 - CPU-Onlytensorflow: CPU - 64 - AlexNetpytorch: CPU - 256 - ResNet-50tensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 256 - GoogLeNettensorflow: CPU - 512 - AlexNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 1 - GoogLeNettensorflow: CPU - 256 - AlexNetab5.163.331067.463.275.233.433327.013.403.4258.7283.435.2512.68385.473.25.679.3520.12841.7719.8521.006.416.4112.8445.5512.9113.035.5536.395.155.461.39321.2151.5312.844.5619.7319.4857.396.4110.8456.55.553.58994.193.055.603.653128.573.603.6262.0493.605.5012.21372.083.095.509.1520.52827.4820.1921.316.326.513.0144.9612.7513.195.4936.025.15.511.38319.3151.2512.904.5419.819.5357.56.4210.8356.55OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lba1.24882.49763.74644.99526.2445.555.16MIN: 5.16 / MAX: 5.76MIN: 4.63 / MAX: 5.38

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lba0.80551.6112.41653.2224.02753.583.33MIN: 3.45 / MAX: 3.76MIN: 3.07 / MAX: 3.54

Blender

Blend File: Pabellon Barcelona - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Pabellon Barcelona - Compute: CPU-Onlyba2004006008001000994.191067.46

TensorFlow

Device: CPU - Batch Size: 32 - Model: VGG-16

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: VGG-16ab0.73581.47162.20742.94323.6793.273.05

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-152ba1.262.523.785.046.35.605.23MIN: 4.7 / MAX: 5.82MIN: 4.63 / MAX: 5.55

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lba0.82131.64262.46393.28524.10653.653.43MIN: 3.29 / MAX: 3.78MIN: 3.22 / MAX: 3.62

Blender

Blend File: Barbershop - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Barbershop - Compute: CPU-Onlyba70014002100280035003128.573327.01

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lba0.811.622.433.244.053.603.40MIN: 3.43 / MAX: 3.75MIN: 3.17 / MAX: 3.52

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lba0.81451.6292.44353.2584.07253.623.42MIN: 3.48 / MAX: 3.74MIN: 3.31 / MAX: 3.62

Timed Mesa Compilation

Time To Compile

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Mesa Compilation 24.0Time To Compileab142842567058.7362.05

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lba0.811.622.433.244.053.603.43MIN: 3.45 / MAX: 3.74MIN: 3.08 / MAX: 3.65

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ba1.23752.4753.71254.956.18755.505.25MIN: 5.23 / MAX: 5.75MIN: 4.56 / MAX: 5.61

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-50ab369121512.6812.21MIN: 11.1 / MAX: 13.05MIN: 11.73 / MAX: 12.93

Blender

Blend File: Fishy Cat - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Fishy Cat - Compute: CPU-Onlyba80160240320400372.08385.47

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: VGG-16ab0.721.442.162.883.63.203.09

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ab1.27582.55163.82745.10326.3795.675.50MIN: 4.92 / MAX: 5.85MIN: 4.52 / MAX: 5.67

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ab36912159.359.15MIN: 8.95 / MAX: 9.56MIN: 7.71 / MAX: 9.45

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: GoogLeNetba51015202520.5220.12

Blender

Blend File: Classroom - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Classroom - Compute: CPU-Onlyba2004006008001000827.48841.77

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: GoogLeNetba51015202520.1919.85

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ba51015202521.3121.00MIN: 19.02 / MAX: 22.37MIN: 18.97 / MAX: 22.06

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab2468106.416.32

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: ResNet-50ba2468106.506.41

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ba369121513.0112.84MIN: 10.31 / MAX: 13.63MIN: 11.98 / MAX: 13.14

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: AlexNetab102030405045.5544.96

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab369121512.9112.75MIN: 12.22 / MAX: 13.13MIN: 11.96 / MAX: 13.06

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ba369121513.1913.03MIN: 12.63 / MAX: 13.62MIN: 10.67 / MAX: 13.24

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ab1.24882.49763.74644.99526.2445.555.49MIN: 5.27 / MAX: 5.69MIN: 4.9 / MAX: 5.65

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: AlexNetab81624324036.3936.02

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: AlexNetab1.15882.31763.47644.63525.7945.155.10

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152ba1.23982.47963.71944.95926.1995.515.46MIN: 4.73 / MAX: 5.69MIN: 5.13 / MAX: 5.76

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: VGG-16ab0.31280.62560.93841.25121.5641.391.38

Blender

Blend File: BMW27 - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: BMW27 - Compute: CPU-Onlyba70140210280350319.31321.21

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: AlexNetab122436486051.5351.25

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ba369121512.9012.84MIN: 11.21 / MAX: 13.23MIN: 11.4 / MAX: 13.12

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab1.0262.0523.0784.1045.134.564.54

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: GoogLeNetba51015202519.8019.73

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 256 - Model: GoogLeNetba51015202519.5319.48

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 512 - Model: AlexNetba132639526557.5057.39

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: ResNet-50ba2468106.426.41

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: GoogLeNetab369121510.8410.83

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 256 - Model: AlexNetba132639526556.5556.50


Phoronix Test Suite v10.8.5