fghj AMD Ryzen 9 5900HX testing with a ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS) and ASUS AMD Cezanne 512MB on Ubuntu 22.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2401107-PTS-FGHJ244998&export=txt&grs&sor&rro .
fghj Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution a b c AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores / 16 Threads) ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS) AMD Renoir/Cezanne 2 x 8 GB DDR4-3200MT/s Micron 4ATF1G64HZ-3G2E2 512GB SAMSUNG MZVLQ512HBLU-00B00 ASUS AMD Cezanne 512MB (2500/1000MHz) AMD Navi 21/23 LQ156M1JW25 Realtek RTL8111/8168/8411 + MEDIATEK MT7921 802.11ax PCI Ubuntu 22.10 5.19.0-46-generic (x86_64) GNOME Shell 43.0 X Server 1.21.1.4 + Wayland 4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47) 1.3.224 GCC 12.2.0 ext4 1920x1080 ASUS AMD Cezanne 512MB ASUS AMD Cezanne 512MB (2500/1000MHz) OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/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-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: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0xa50000c - ACPI Profile: balanced Python Details - Python 3.10.7 Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + 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 IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
fghj speedb: Read While Writing pytorch: CPU - 16 - ResNet-50 speedb: Update Rand tensorflow: CPU - 1 - AlexNet tensorflow: CPU - 1 - VGG-16 y-cruncher: 500M tensorflow: CPU - 16 - ResNet-50 tensorflow: CPU - 1 - GoogLeNet pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 1 - Efficientnet_v2_l y-cruncher: 1B tensorflow: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-50 speedb: Seq Fill tensorflow: CPU - 16 - VGG-16 tensorflow: CPU - 16 - AlexNet pytorch: CPU - 1 - ResNet-152 quicksilver: CORAL2 P2 speedb: Rand Read pytorch: CPU - 16 - ResNet-152 tensorflow: CPU - 16 - GoogLeNet speedb: Read Rand Write Rand speedb: Rand Fill quicksilver: CORAL2 P1 quicksilver: CTS2 speedb: Rand Fill Sync a b c 3035137 20.22 458594 4.61 1.43 23.263 7.59 12.17 6.22 9.58 50.423 5.09 34.04 933961 3.5 40.05 15.15 22560000 51459190 9.09 21.12 1769691 819366 11990000 11390000 11900 2842258 18.95 472342 4.69 1.45 23.077 7.65 12.22 6.28 9.46 49.828 5.13 34.44 935621 3.52 40.34 15.27 22713333 51062544 9.07 21.20 1776164 821234 11966667 11406667 6186 2960839 19.76 474392 4.71 1.46 22.894 7.70 12.05 6.30 9.48 49.804 5.15 34.13 944900 3.54 40.40 15.21 22536667 51108888 9.14 21.25 1778569 818673 11953333 11416667 5060 OpenBenchmarking.org
Speedb Test: Read While Writing OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Read While Writing b c a 700K 1400K 2100K 2800K 3500K SE +/- 24784.71, N = 3 SE +/- 41229.39, N = 3 2842258 2960839 3035137 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
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 b c a 5 10 15 20 25 SE +/- 0.25, N = 15 SE +/- 0.21, N = 3 18.95 19.76 20.22 MIN: 14.69 / MAX: 21.46 MIN: 16.58 / MAX: 21.09 MIN: 18.6 / MAX: 20.71
Speedb Test: Update Random OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Update Random a b c 100K 200K 300K 400K 500K SE +/- 842.48, N = 3 SE +/- 1807.73, N = 3 458594 472342 474392 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
TensorFlow Device: CPU - Batch Size: 1 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: AlexNet a b c 1.0598 2.1196 3.1794 4.2392 5.299 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 4.61 4.69 4.71
TensorFlow Device: CPU - Batch Size: 1 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: VGG-16 a b c 0.3285 0.657 0.9855 1.314 1.6425 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 1.43 1.45 1.46
Y-Cruncher Pi Digits To Calculate: 500M OpenBenchmarking.org Seconds, Fewer Is Better Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M a b c 6 12 18 24 30 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 23.26 23.08 22.89
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 a b c 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 7.59 7.65 7.70
TensorFlow Device: CPU - Batch Size: 1 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: GoogLeNet c a b 3 6 9 12 15 SE +/- 0.17, N = 3 SE +/- 0.04, N = 3 12.05 12.17 12.22
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 a b c 2 4 6 8 10 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 6.22 6.28 6.30 MIN: 5.85 / MAX: 6.47 MIN: 5.5 / MAX: 6.59 MIN: 5.7 / MAX: 6.6
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 b c a 3 6 9 12 15 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 9.46 9.48 9.58 MIN: 8.4 / MAX: 9.86 MIN: 8.48 / MAX: 9.81 MIN: 8.52 / MAX: 9.8
Y-Cruncher Pi Digits To Calculate: 1B OpenBenchmarking.org Seconds, Fewer Is Better Y-Cruncher 0.8.3 Pi Digits To Calculate: 1B a b c 11 22 33 44 55 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 50.42 49.83 49.80
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 a b c 1.1588 2.3176 3.4764 4.6352 5.794 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 5.09 5.13 5.15
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 a c b 8 16 24 32 40 SE +/- 0.34, N = 15 SE +/- 0.48, N = 12 34.04 34.13 34.44 MIN: 28.91 / MAX: 36.18 MIN: 26.23 / MAX: 39.87 MIN: 26.93 / MAX: 39.45
Speedb Test: Sequential Fill OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Sequential Fill a b c 200K 400K 600K 800K 1000K SE +/- 2992.09, N = 3 SE +/- 3484.82, N = 3 933961 935621 944900 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
TensorFlow Device: CPU - Batch Size: 16 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 a b c 0.7965 1.593 2.3895 3.186 3.9825 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 3.50 3.52 3.54
TensorFlow Device: CPU - Batch Size: 16 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: AlexNet a b c 9 18 27 36 45 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 40.05 40.34 40.40
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 a c b 4 8 12 16 20 SE +/- 0.08, N = 3 SE +/- 0.12, N = 3 15.15 15.21 15.27 MIN: 13.55 / MAX: 16.17 MIN: 13.44 / MAX: 16.4 MIN: 12.92 / MAX: 16.47
Quicksilver Input: CORAL2 P2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P2 c a b 5M 10M 15M 20M 25M SE +/- 39299.42, N = 3 SE +/- 102034.85, N = 3 22536667 22560000 22713333 1. (CXX) g++ options: -fopenmp -O3 -march=native
Speedb Test: Random Read OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Read b c a 11M 22M 33M 44M 55M SE +/- 51114.25, N = 3 SE +/- 78995.12, N = 3 51062544 51108888 51459190 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
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 b a c 3 6 9 12 15 SE +/- 0.07, N = 12 SE +/- 0.08, N = 12 9.07 9.09 9.14 MIN: 7.85 / MAX: 10 MIN: 8.47 / MAX: 9.73 MIN: 6.86 / MAX: 9.99
TensorFlow Device: CPU - Batch Size: 16 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: GoogLeNet a b c 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 21.12 21.20 21.25
Speedb Test: Read Random Write Random OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Read Random Write Random a b c 400K 800K 1200K 1600K 2000K SE +/- 3532.02, N = 3 SE +/- 579.88, N = 3 1769691 1776164 1778569 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
Speedb Test: Random Fill OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Fill c a b 200K 400K 600K 800K 1000K SE +/- 2403.56, N = 3 SE +/- 1525.32, N = 3 818673 819366 821234 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
Quicksilver Input: CORAL2 P1 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P1 c b a 3M 6M 9M 12M 15M SE +/- 12018.50, N = 3 SE +/- 17638.34, N = 3 11953333 11966667 11990000 1. (CXX) g++ options: -fopenmp -O3 -march=native
Quicksilver Input: CTS2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CTS2 a b c 2M 4M 6M 8M 10M SE +/- 23333.33, N = 3 SE +/- 13333.33, N = 3 11390000 11406667 11416667 1. (CXX) g++ options: -fopenmp -O3 -march=native
Speedb Test: Random Fill Sync OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Fill Sync c b a 3K 6K 9K 12K 15K SE +/- 513.98, N = 15 SE +/- 436.52, N = 15 5060 6186 11900 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
Phoronix Test Suite v10.8.5