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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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2403275-NE-TESTS110635
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March 26
  5 Hours, 17 Minutes
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March 26
  5 Hours, 11 Minutes
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testsOpenBenchmarking.orgPhoronix Test SuiteAMD 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 11.4.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionTests PerformanceSystem Logs- Transparent Huge Pages: madvise- --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 - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0x8608103 - Python 3.10.12- 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

a vs. b ComparisonPhoronix Test SuiteBaseline+1.9%+1.9%+3.8%+3.8%+5.7%+5.7%+7.6%+7.6%7.6%7.5%7.4%7.1%6.4%6.3%5.9%5.8%5%4.8%3.6%2%CPU - 1 - Efficientnet_v2_lCPU - 256 - Efficientnet_v2_lPabellon Barcelona - CPU-OnlyCPU - 32 - VGG-167.2%CPU - 512 - ResNet-152CPU - 16 - Efficientnet_v2_lBarbershop - CPU-OnlyCPU - 32 - Efficientnet_v2_lCPU - 64 - Efficientnet_v2_lTime To Compile5.7%CPU - 512 - Efficientnet_v2_lCPU - 256 - ResNet-152CPU - 512 - ResNet-503.8%Fishy Cat - CPU-OnlyCPU - 16 - VGG-163.6%CPU - 16 - ResNet-1523.1%CPU - 1 - ResNet-1522.2%CPU - 32 - GoogLeNetPyTorchPyTorchBlenderTensorFlowPyTorchPyTorchBlenderPyTorchPyTorchTimed Mesa CompilationPyTorchPyTorchPyTorchBlenderTensorFlowPyTorchPyTorchTensorFlowab

testsbuild-mesa: Time To Compiletensorflow: CPU - 1 - VGG-16tensorflow: CPU - 1 - AlexNettensorflow: CPU - 16 - VGG-16tensorflow: CPU - 32 - VGG-16tensorflow: CPU - 16 - AlexNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 64 - AlexNettensorflow: CPU - 1 - GoogLeNettensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 256 - AlexNettensorflow: CPU - 512 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 256 - GoogLeNetblender: BMW27 - CPU-Onlyblender: Classroom - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Barbershop - CPU-Onlyblender: Pabellon Barcelona - CPU-Onlypytorch: 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 - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lab58.7281.395.153.23.2736.3945.5551.5310.844.5656.557.3919.856.4120.126.4119.736.4119.48321.21841.77385.473327.011067.4621.009.3513.0312.8412.915.6712.845.5512.685.465.255.235.163.433.403.423.333.4362.0491.385.13.093.0536.0244.9651.2510.834.5456.5557.520.196.520.526.4219.86.3219.53319.31827.48372.083128.57994.1921.319.1513.1913.0112.755.5012.905.4912.215.515.505.605.553.653.603.623.583.60OpenBenchmarking.org

Timed Mesa Compilation

This test profile times how long it takes to compile Mesa with Meson/Ninja. For minimizing build dependencies and avoid versioning conflicts, test this is just the core Mesa build without LLVM or the extra Gallium3D/Mesa drivers enabled. Learn more via the OpenBenchmarking.org test page.

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

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

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

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

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

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

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

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Learn more via the OpenBenchmarking.org test page.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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