tpy AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA NV174 8GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2401073-PTS-TPY9619764&gru&sor .
tpy Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL Compiler File-System Screen Resolution a b c d AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads) ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) AMD Device 14d8 32GB 2000GB Samsung SSD 980 PRO 2TB + 4001GB Western Digital WD_BLACK SN850X 4000GB NVIDIA NV174 8GB NVIDIA GA104 HD Audio DELL U2723QE Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 Ubuntu 23.10 6.7.0-060700rc2daily20231127-generic (x86_64) GNOME Shell 45.1 X Server 1.21.1.7 + Wayland nouveau 4.3 Mesa 24.0~git2311260600.945288~oibaf~m (git-945288f 2023-11-26 mantic-oibaf-ppa) GCC 13.2.0 + LLVM 16.0.6 ext4 3840x2160 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,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-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/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-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: 0xa601203 Python Details - Python 3.11.6 Security 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: Not affected + spec_rstack_overflow: Vulnerable: Safe RET no microcode + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
tpy 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 quicksilver: CTS2 quicksilver: CORAL2 P1 quicksilver: CORAL2 P2 tensorflow: CPU - 1 - VGG-16 tensorflow: CPU - 1 - AlexNet tensorflow: CPU - 16 - VGG-16 tensorflow: CPU - 16 - AlexNet tensorflow: CPU - 1 - GoogLeNet tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 16 - GoogLeNet tensorflow: CPU - 16 - ResNet-50 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 y-cruncher: 1B y-cruncher: 5B y-cruncher: 500M a b c d 75.35 31.52 50.47 21.04 16.63 12.60 21000000 25220000 25790000 5.66 15.99 18.86 175.11 53.74 14.58 144.31 42.72 954442 147210519 685228 981469 3763 5742331 3121462 16.673 100.858 7.967 75.88 31.43 50.64 20.93 16.92 12.54 21010000 25120000 25790000 5.67 15.97 18.84 175.03 54.38 14.59 143.92 42.64 939009 146512383 685969 979943 3753 5429438 3139533 16.798 101.087 7.967 76.25 30.27 49.49 20.91 16.61 12.59 20880000 25110000 25760000 5.66 16.04 18.83 175.11 53.71 14.63 144.06 42.76 952620 146079090 689457 989483 3737 5484728 3144190 16.817 101.153 7.963 74.61 29.64 50.46 21.03 16.79 12.63 20930000 25020000 25710000 5.66 16.01 18.8 175.08 54.04 14.63 144.18 42.68 937049 145109573 686870 986432 3645 5554254 3154171 16.833 100.931 8.025 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 a d 20 40 60 80 100 76.25 75.88 75.35 74.61 MIN: 71.8 / MAX: 76.63 MIN: 70.68 / MAX: 76.3 MIN: 67.9 / MAX: 75.94 MIN: 71.96 / MAX: 75.09
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 d 7 14 21 28 35 31.52 31.43 30.27 29.64 MIN: 24.51 / MAX: 31.66 MIN: 30.82 / MAX: 31.61 MIN: 29.6 / MAX: 30.45 MIN: 29.28 / MAX: 29.84
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 a d c 11 22 33 44 55 50.64 50.47 50.46 49.49 MIN: 48.46 / MAX: 51.27 MIN: 48.54 / MAX: 50.92 MIN: 48.93 / MAX: 50.78 MIN: 48.22 / MAX: 50.61
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 d b c 5 10 15 20 25 21.04 21.03 20.93 20.91 MIN: 20.73 / MAX: 21.12 MIN: 20.56 / MAX: 21.17 MIN: 20.62 / MAX: 21.04 MIN: 20.48 / MAX: 21.09
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 d a c 4 8 12 16 20 16.92 16.79 16.63 16.61 MIN: 16.73 / MAX: 17 MIN: 16.64 / MAX: 16.93 MIN: 16.28 / MAX: 16.69 MIN: 16.37 / MAX: 16.69
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 d a c b 3 6 9 12 15 12.63 12.60 12.59 12.54 MIN: 11.07 / MAX: 12.99 MIN: 10.82 / MAX: 12.88 MIN: 10.67 / MAX: 12.87 MIN: 10.77 / MAX: 12.85
Quicksilver Input: CTS2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CTS2 b a d c 4M 8M 12M 16M 20M 21010000 21000000 20930000 20880000 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 a b c d 5M 10M 15M 20M 25M 25220000 25120000 25110000 25020000 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 b a c d 6M 12M 18M 24M 30M 25790000 25790000 25760000 25710000 1. (CXX) g++ options: -fopenmp -O3 -march=native
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 b d c a 1.2758 2.5516 3.8274 5.1032 6.379 5.67 5.66 5.66 5.66
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 c d a b 4 8 12 16 20 16.04 16.01 15.99 15.97
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 d 5 10 15 20 25 18.86 18.84 18.83 18.80
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 c a d b 40 80 120 160 200 175.11 175.11 175.08 175.03
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 b d a c 12 24 36 48 60 54.38 54.04 53.74 53.71
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 d c b a 4 8 12 16 20 14.63 14.63 14.59 14.58
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 d c b 30 60 90 120 150 144.31 144.18 144.06 143.92
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 a d b 10 20 30 40 50 42.76 42.72 42.68 42.64
Speedb Test: Random Fill OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Fill a c b d 200K 400K 600K 800K 1000K 954442 952620 939009 937049 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 d 30M 60M 90M 120M 150M 147210519 146512383 146079090 145109573 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 c d b a 150K 300K 450K 600K 750K 689457 686870 685969 685228 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 c d a b 200K 400K 600K 800K 1000K 989483 986432 981469 979943 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 d 800 1600 2400 3200 4000 3763 3753 3737 3645 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 d c b 1.2M 2.4M 3.6M 4.8M 6M 5742331 5554254 5484728 5429438 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 d c b a 700K 1400K 2100K 2800K 3500K 3154171 3144190 3139533 3121462 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
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 d 4 8 12 16 20 16.67 16.80 16.82 16.83
Y-Cruncher Pi Digits To Calculate: 5B OpenBenchmarking.org Seconds, Fewer Is Better Y-Cruncher 0.8.3 Pi Digits To Calculate: 5B a d b c 20 40 60 80 100 100.86 100.93 101.09 101.15
Y-Cruncher Pi Digits To Calculate: 500M OpenBenchmarking.org Seconds, Fewer Is Better Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M c a b d 2 4 6 8 10 7.963 7.967 7.967 8.025
Phoronix Test Suite v10.8.4