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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2401073-PTS-TPY9619764 tpy - Phoronix Test Suite 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&grs&rdt&rro .
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-152 speedb: Read While Writing speedb: Rand Fill Sync pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - Efficientnet_v2_l speedb: Rand Fill speedb: Rand Read tensorflow: CPU - 1 - GoogLeNet speedb: Read Rand Write Rand speedb: Seq Fill y-cruncher: 1B quicksilver: CORAL2 P1 y-cruncher: 500M pytorch: CPU - 16 - Efficientnet_v2_l quicksilver: CTS2 pytorch: CPU - 16 - ResNet-152 speedb: Update Rand tensorflow: CPU - 1 - AlexNet tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 16 - VGG-16 quicksilver: CORAL2 P2 y-cruncher: 5B tensorflow: CPU - 16 - ResNet-50 tensorflow: CPU - 16 - GoogLeNet tensorflow: CPU - 1 - VGG-16 tensorflow: CPU - 16 - AlexNet a b c d 31.52 5742331 3763 50.47 75.35 16.63 954442 147210519 53.74 3121462 981469 16.673 25220000 7.967 12.60 21000000 21.04 685228 15.99 14.58 18.86 25790000 100.858 42.72 144.31 5.66 175.11 31.43 5429438 3753 50.64 75.88 16.92 939009 146512383 54.38 3139533 979943 16.798 25120000 7.967 12.54 21010000 20.93 685969 15.97 14.59 18.84 25790000 101.087 42.64 143.92 5.67 175.03 30.27 5484728 3737 49.49 76.25 16.61 952620 146079090 53.71 3144190 989483 16.817 25110000 7.963 12.59 20880000 20.91 689457 16.04 14.63 18.83 25760000 101.153 42.76 144.06 5.66 175.11 29.64 5554254 3645 50.46 74.61 16.79 937049 145109573 54.04 3154171 986432 16.833 25020000 8.025 12.63 20930000 21.03 686870 16.01 14.63 18.8 25710000 100.931 42.68 144.18 5.66 175.08 OpenBenchmarking.org
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 d c b a 7 14 21 28 35 29.64 30.27 31.43 31.52 MIN: 29.28 / MAX: 29.84 MIN: 29.6 / MAX: 30.45 MIN: 30.82 / MAX: 31.61 MIN: 24.51 / MAX: 31.66
Speedb Test: Read While Writing OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Read While Writing d c b a 1.2M 2.4M 3.6M 4.8M 6M 5554254 5484728 5429438 5742331 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 d c b a 800 1600 2400 3200 4000 3645 3737 3753 3763 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 d c b a 11 22 33 44 55 50.46 49.49 50.64 50.47 MIN: 48.93 / MAX: 50.78 MIN: 48.22 / MAX: 50.61 MIN: 48.46 / MAX: 51.27 MIN: 48.54 / MAX: 50.92
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 d c b a 20 40 60 80 100 74.61 76.25 75.88 75.35 MIN: 71.96 / MAX: 75.09 MIN: 71.8 / MAX: 76.63 MIN: 70.68 / MAX: 76.3 MIN: 67.9 / MAX: 75.94
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 d c b a 4 8 12 16 20 16.79 16.61 16.92 16.63 MIN: 16.64 / MAX: 16.93 MIN: 16.37 / MAX: 16.69 MIN: 16.73 / MAX: 17 MIN: 16.28 / MAX: 16.69
Speedb Test: Random Fill OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Random Fill d c b a 200K 400K 600K 800K 1000K 937049 952620 939009 954442 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 d c b a 30M 60M 90M 120M 150M 145109573 146079090 146512383 147210519 1. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread
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 d c b a 12 24 36 48 60 54.04 53.71 54.38 53.74
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
Speedb Test: Sequential Fill OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Sequential Fill d c b a 200K 400K 600K 800K 1000K 986432 989483 979943 981469 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 d c b a 4 8 12 16 20 16.83 16.82 16.80 16.67
Quicksilver Input: CORAL2 P1 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P1 d c b a 5M 10M 15M 20M 25M 25020000 25110000 25120000 25220000 1. (CXX) g++ options: -fopenmp -O3 -march=native
Y-Cruncher Pi Digits To Calculate: 500M OpenBenchmarking.org Seconds, Fewer Is Better Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M d c b a 2 4 6 8 10 8.025 7.963 7.967 7.967
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 c b a 3 6 9 12 15 12.63 12.59 12.54 12.60 MIN: 11.07 / MAX: 12.99 MIN: 10.67 / MAX: 12.87 MIN: 10.77 / MAX: 12.85 MIN: 10.82 / MAX: 12.88
Quicksilver Input: CTS2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CTS2 d c b a 4M 8M 12M 16M 20M 20930000 20880000 21010000 21000000 1. (CXX) g++ options: -fopenmp -O3 -march=native
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 d c b a 5 10 15 20 25 21.03 20.91 20.93 21.04 MIN: 20.56 / MAX: 21.17 MIN: 20.48 / MAX: 21.09 MIN: 20.62 / MAX: 21.04 MIN: 20.73 / MAX: 21.12
Speedb Test: Update Random OpenBenchmarking.org Op/s, More Is Better Speedb 2.7 Test: Update Random d c b a 150K 300K 450K 600K 750K 686870 689457 685969 685228 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 d c b a 4 8 12 16 20 16.01 16.04 15.97 15.99
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: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 d c b a 5 10 15 20 25 18.80 18.83 18.84 18.86
Quicksilver Input: CORAL2 P2 OpenBenchmarking.org Figure Of Merit, More Is Better Quicksilver 20230818 Input: CORAL2 P2 d c b a 6M 12M 18M 24M 30M 25710000 25760000 25790000 25790000 1. (CXX) g++ options: -fopenmp -O3 -march=native
Y-Cruncher Pi Digits To Calculate: 5B OpenBenchmarking.org Seconds, Fewer Is Better Y-Cruncher 0.8.3 Pi Digits To Calculate: 5B d c b a 20 40 60 80 100 100.93 101.15 101.09 100.86
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 d c b a 10 20 30 40 50 42.68 42.76 42.64 42.72
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 d c b a 30 60 90 120 150 144.18 144.06 143.92 144.31
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 d c b a 1.2758 2.5516 3.8274 5.1032 6.379 5.66 5.66 5.67 5.66
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 d c b a 40 80 120 160 200 175.08 175.11 175.03 175.11
Phoronix Test Suite v10.8.4