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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2401107-PTS-FGHJ244998 fghj - Phoronix Test Suite 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&grw&sro .
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 y-cruncher: 500M y-cruncher: 1B tensorflow: CPU - 1 - VGG-16 quicksilver: CORAL2 P2 tensorflow: CPU - 1 - AlexNet tensorflow: CPU - 16 - VGG-16 quicksilver: CORAL2 P1 tensorflow: CPU - 16 - AlexNet tensorflow: CPU - 1 - GoogLeNet tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 16 - GoogLeNet tensorflow: CPU - 16 - ResNet-50 pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l speedb: Rand Fill speedb: Rand Read speedb: Update Rand speedb: Seq Fill speedb: Rand Fill Sync speedb: Read While Writing speedb: Read Rand Write Rand quicksilver: CTS2 a b c 23.263 50.423 1.43 22560000 4.61 3.5 11990000 40.05 12.17 5.09 21.12 7.59 34.04 15.15 20.22 9.09 9.58 6.22 819366 51459190 458594 933961 11900 3035137 1769691 11390000 23.077 49.828 1.45 22713333 4.69 3.52 11966667 40.34 12.22 5.13 21.20 7.65 34.44 15.27 18.95 9.07 9.46 6.28 821234 51062544 472342 935621 6186 2842258 1776164 11406667 22.894 49.804 1.46 22536667 4.71 3.54 11953333 40.40 12.05 5.15 21.25 7.70 34.13 15.21 19.76 9.14 9.48 6.30 818673 51108888 474392 944900 5060 2960839 1778569 11416667 OpenBenchmarking.org
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
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: 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
Quicksilver Input: CORAL2 P2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P2 a b c 5M 10M 15M 20M 25M SE +/- 102034.85, N = 3 SE +/- 39299.42, N = 3 22560000 22713333 22536667 1. (CXX) g++ options: -fopenmp -O3 -march=native
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: 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
Quicksilver Input: CORAL2 P1 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P1 a b c 3M 6M 9M 12M 15M SE +/- 17638.34, N = 3 SE +/- 12018.50, N = 3 11990000 11966667 11953333 1. (CXX) g++ options: -fopenmp -O3 -march=native
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
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 a b c 3 6 9 12 15 SE +/- 0.04, N = 3 SE +/- 0.17, N = 3 12.17 12.22 12.05
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
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
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
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 b c 8 16 24 32 40 SE +/- 0.48, N = 12 SE +/- 0.34, N = 15 34.04 34.44 34.13 MIN: 28.91 / MAX: 36.18 MIN: 26.93 / MAX: 39.45 MIN: 26.23 / MAX: 39.87
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 b c 4 8 12 16 20 SE +/- 0.12, N = 3 SE +/- 0.08, N = 3 15.15 15.27 15.21 MIN: 13.55 / MAX: 16.17 MIN: 12.92 / MAX: 16.47 MIN: 13.44 / MAX: 16.4
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 a b c 5 10 15 20 25 SE +/- 0.25, N = 15 SE +/- 0.21, N = 3 20.22 18.95 19.76 MIN: 18.6 / MAX: 20.71 MIN: 14.69 / MAX: 21.46 MIN: 16.58 / MAX: 21.09
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 a b c 3 6 9 12 15 SE +/- 0.07, N = 12 SE +/- 0.08, N = 12 9.09 9.07 9.14 MIN: 8.47 / MAX: 9.73 MIN: 7.85 / MAX: 10 MIN: 6.86 / MAX: 9.99
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 a b c 3 6 9 12 15 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 9.58 9.46 9.48 MIN: 8.52 / MAX: 9.8 MIN: 8.4 / MAX: 9.86 MIN: 8.48 / MAX: 9.81
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
Speedb Test: Random Fill OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Fill a b c 200K 400K 600K 800K 1000K SE +/- 1525.32, N = 3 SE +/- 2403.56, N = 3 819366 821234 818673 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
Speedb Test: Random Read OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Read a b c 11M 22M 33M 44M 55M SE +/- 51114.25, N = 3 SE +/- 78995.12, N = 3 51459190 51062544 51108888 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
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
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
Speedb Test: Random Fill Sync OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Fill Sync a b c 3K 6K 9K 12K 15K SE +/- 436.52, N = 15 SE +/- 513.98, N = 15 11900 6186 5060 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
Speedb Test: Read While Writing OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Read While Writing a b c 700K 1400K 2100K 2800K 3500K SE +/- 24784.71, N = 3 SE +/- 41229.39, N = 3 3035137 2842258 2960839 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
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
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
Phoronix Test Suite v10.8.4