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 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&grt&rdt&rro .
fhd Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution s b c AMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads) NB01 NL5xNU (1.07.11RTR1 BIOS) AMD Renoir/Cezanne 16GB Samsung SSD 970 EVO Plus 500GB AMD Lucienne 512MB (1800/400MHz) AMD Renoir Radeon HD Audio Realtek RTL8111/8168/8411 + Intel Wi-Fi 6 AX200 Tuxedo 22.04 6.0.0-1010-oem (x86_64) KDE Plasma 5.26.5 X Server 1.21.1.3 4.6 Mesa 22.3.7 (LLVM 14.0.0 DRM 3.48) 1.3.230 GCC 11.3.0 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler 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 3.10.6 Security 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
fhd pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 64 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 64 - Efficientnet_v2_l quicksilver: CTS2 quicksilver: CORAL2 P1 quicksilver: CORAL2 P2 tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 16 - ResNet-50 tensorflow: CPU - 32 - ResNet-50 tensorflow: CPU - 64 - ResNet-50 s b c 18.08 7.34 9.88 9.93 10.00 4.24 4.24 4.21 4.88 2.96 2.98 3.01 5801667 6085667 11386667 4.35 6.55 6.66 6.67 18.61 7.57 10.13 10.38 10.10 4.35 4.28 4.34 4.95 3.00 2.97 2.97 5815000 6090000 11390000 4.28 6.49 6.64 6.68 17.68 7.48 10.05 10.10 10.05 4.27 4.22 4.33 4.92 3.00 3.01 3.04 5770000 6071000 11370000 4.28 6.47 6.63 6.68 OpenBenchmarking.org
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 c b s 5 10 15 20 25 SE +/- 0.14, N = 3 17.68 18.61 18.08 MIN: 12.28 / MAX: 21.23 MIN: 16.39 / MAX: 21.61 MIN: 15.84 / MAX: 21.76
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 c b s 2 4 6 8 10 SE +/- 0.05, N = 3 7.48 7.57 7.34 MIN: 4.76 / MAX: 9.16 MIN: 4.43 / MAX: 9.03 MIN: 4.67 / MAX: 9.47
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 c b s 3 6 9 12 15 SE +/- 0.06, N = 3 10.05 10.13 9.88 MIN: 5.43 / MAX: 11.83 MIN: 6.6 / MAX: 12.34 MIN: 5.98 / MAX: 12.22
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 c b s 3 6 9 12 15 SE +/- 0.04, N = 3 10.10 10.38 9.93 MIN: 6.02 / MAX: 12.08 MIN: 7.09 / MAX: 12.44 MIN: 6.31 / MAX: 12.54
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 c b s 3 6 9 12 15 SE +/- 0.11, N = 5 10.05 10.10 10.00 MIN: 5.43 / MAX: 12.02 MIN: 6.91 / MAX: 12.22 MIN: 5.78 / MAX: 12.3
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 c b s 0.9788 1.9576 2.9364 3.9152 4.894 SE +/- 0.03, N = 3 4.27 4.35 4.24 MIN: 2.71 / MAX: 5.35 MIN: 2.67 / MAX: 5.28 MIN: 2.77 / MAX: 5.36
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 c b s 0.963 1.926 2.889 3.852 4.815 SE +/- 0.00, N = 3 4.22 4.28 4.24 MIN: 2.82 / MAX: 5.35 MIN: 2.77 / MAX: 5.34 MIN: 2.69 / MAX: 5.49
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 c b s 0.9765 1.953 2.9295 3.906 4.8825 SE +/- 0.05, N = 3 4.33 4.34 4.21 MIN: 2.76 / MAX: 5.39 MIN: 2.83 / MAX: 5.5 MIN: 2.71 / MAX: 5.3
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l c b s 1.1138 2.2276 3.3414 4.4552 5.569 SE +/- 0.03, N = 3 4.92 4.95 4.88 MIN: 4.35 / MAX: 5.62 MIN: 4.2 / MAX: 5.61 MIN: 3.43 / MAX: 5.79
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l c b s 0.675 1.35 2.025 2.7 3.375 SE +/- 0.03, N = 3 3.00 3.00 2.96 MIN: 2.06 / MAX: 3.49 MIN: 2.07 / MAX: 3.61 MIN: 2 / MAX: 3.69
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l c b s 0.6773 1.3546 2.0319 2.7092 3.3865 SE +/- 0.01, N = 3 3.01 2.97 2.98 MIN: 2.1 / MAX: 3.55 MIN: 2.06 / MAX: 3.53 MIN: 1.88 / MAX: 3.59
PyTorch Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l c b s 0.684 1.368 2.052 2.736 3.42 SE +/- 0.00, N = 3 3.04 2.97 3.01 MIN: 2 / MAX: 3.59 MIN: 2 / MAX: 3.54 MIN: 2 / MAX: 3.67
Quicksilver Input: CTS2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CTS2 c b s 1.2M 2.4M 3.6M 4.8M 6M SE +/- 13169.83, N = 3 5770000 5815000 5801667 1. (CXX) g++ options: -fopenmp -O3 -march=native
Quicksilver Input: CORAL2 P1 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P1 c b s 1.3M 2.6M 3.9M 5.2M 6.5M SE +/- 13920.41, N = 3 6071000 6090000 6085667 1. (CXX) g++ options: -fopenmp -O3 -march=native
Quicksilver Input: CORAL2 P2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P2 c b s 2M 4M 6M 8M 10M SE +/- 29059.33, N = 3 11370000 11390000 11386667 1. (CXX) g++ options: -fopenmp -O3 -march=native
TensorFlow Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: ResNet-50 c b s 0.9788 1.9576 2.9364 3.9152 4.894 SE +/- 0.00, N = 3 4.28 4.28 4.35
TensorFlow Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: ResNet-50 c b s 2 4 6 8 10 SE +/- 0.00, N = 3 6.47 6.49 6.55
TensorFlow Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 32 - Model: ResNet-50 c b s 2 4 6 8 10 SE +/- 0.01, N = 3 6.63 6.64 6.66
TensorFlow Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 64 - Model: ResNet-50 c b s 2 4 6 8 10 SE +/- 0.01, N = 3 6.68 6.68 6.67
Phoronix Test Suite v10.8.4