AMD Ryzen 5 5500U testing with a LENOVO LNVNB161216 (GLCN22WW BIOS) and AMD Lucienne 2GB on Ubuntu 21.10 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 2203306-PTS-ONEDNN5567 onednn 5500U - Phoronix Test Suite onednn 5500U AMD Ryzen 5 5500U testing with a LENOVO LNVNB161216 (GLCN22WW BIOS) and AMD Lucienne 2GB on Ubuntu 21.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2203306-PTS-ONEDNN5567&sor&grs .
onednn 5500U Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution A B C AMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads) LENOVO LNVNB161216 (GLCN22WW BIOS) AMD Renoir/Cezanne 6GB 256GB SAMSUNG MZALQ256HBJD-00BL2 AMD Lucienne 2GB (1800/400MHz) AMD Renoir Radeon HD Audio Qualcomm Atheros QCA6174 802.11ac Ubuntu 21.10 5.17.0-051700-generic (x86_64) GNOME Shell 40.5 X Server 1.20.13 + Wayland 4.6 Mesa 22.1.0-devel (git-729f95a 2022-03-24 impish-oibaf-ppa) (LLVM 13.0.1 DRM 3.44) 1.3.207 GCC 11.2.0 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-ZPT0kp/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-ZPT0kp/gcc-11-11.2.0/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 schedutil (Boost: Enabled) - CPU Microcode: 0x8608102 Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
onednn 5500U onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: IP Shapes 1D - f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: IP Shapes 1D - bf16bf16bf16 - CPU A B C 14.5003 4.55304 13.6222 3.72999 5.62842 7127.16 34.4526 7.90632 4687.06 4694.72 7099.28 7073.68 11.7557 12.1054 5.11790 8.03215 4688.21 37.7711 11.3258 3.75469 13.6417 3.79690 5.61911 7087.03 34.1244 7.89074 4683.43 4701.50 7098.27 7067.16 11.7185 12.0876 5.11311 8.02814 4690.55 33.7365 11.3864 3.76327 13.3253 3.79445 5.70647 7043.60 34.1586 7.85276 4662.02 4676.62 7066.77 7094.51 11.7205 12.0864 5.11709 8.03124 4690.50 33.7210 OpenBenchmarking.org
oneDNN Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU B C A 4 8 12 16 20 SE +/- 0.06, N = 3 SE +/- 0.04, N = 3 SE +/- 0.00, N = 3 11.33 11.39 14.50 MIN: 11.07 MIN: 11.16 MIN: 14.37 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU B C A 1.0244 2.0488 3.0732 4.0976 5.122 SE +/- 0.04023, N = 5 SE +/- 0.05002, N = 3 SE +/- 0.00367, N = 3 3.75469 3.76327 4.55304 MIN: 3.55 MIN: 3.58 MIN: 4.49 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU C A B 4 8 12 16 20 SE +/- 0.17, N = 15 SE +/- 0.14, N = 15 SE +/- 0.13, N = 15 13.33 13.62 13.64 MIN: 9.03 MIN: 8.96 MIN: 9 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU A C B 0.8543 1.7086 2.5629 3.4172 4.2715 SE +/- 0.03657, N = 3 SE +/- 0.03002, N = 3 SE +/- 0.02821, N = 3 3.72999 3.79445 3.79690 MIN: 3.5 MIN: 3.4 MIN: 3.57 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU B A C 1.284 2.568 3.852 5.136 6.42 SE +/- 0.06253, N = 5 SE +/- 0.05563, N = 6 SE +/- 0.05850, N = 12 5.61911 5.62842 5.70647 MIN: 4.89 MIN: 5.07 MIN: 4.88 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU C B A 1500 3000 4500 6000 7500 SE +/- 14.12, N = 3 SE +/- 9.99, N = 3 SE +/- 8.00, N = 3 7043.60 7087.03 7127.16 MIN: 6995.5 MIN: 7040.89 MIN: 7078.19 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU B C A 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 34.12 34.16 34.45 MIN: 33.66 MIN: 33.59 MIN: 34.09 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU C B A 2 4 6 8 10 SE +/- 0.00587, N = 3 SE +/- 0.01478, N = 3 SE +/- 0.01256, N = 3 7.85276 7.89074 7.90632 MIN: 7.73 MIN: 7.75 MIN: 7.78 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU C B A 1000 2000 3000 4000 5000 SE +/- 5.70, N = 3 SE +/- 9.44, N = 3 SE +/- 8.81, N = 3 4662.02 4683.43 4687.06 MIN: 4631.35 MIN: 4644.98 MIN: 4647.19 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU C A B 1000 2000 3000 4000 5000 SE +/- 15.17, N = 3 SE +/- 12.56, N = 3 SE +/- 20.21, N = 3 4676.62 4694.72 4701.50 MIN: 4628.39 MIN: 4650.38 MIN: 4642.31 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU C B A 1500 3000 4500 6000 7500 SE +/- 7.85, N = 3 SE +/- 10.05, N = 3 SE +/- 16.66, N = 3 7066.77 7098.27 7099.28 MIN: 7019.15 MIN: 7058.13 MIN: 7031.56 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU B A C 1500 3000 4500 6000 7500 SE +/- 12.42, N = 3 SE +/- 5.15, N = 3 SE +/- 12.08, N = 3 7067.16 7073.68 7094.51 MIN: 7017.84 MIN: 7037.09 MIN: 7042.1 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU B C A 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 11.72 11.72 11.76 MIN: 11.49 MIN: 11.51 MIN: 11.4 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU C B A 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 12.09 12.09 12.11 MIN: 11.63 MIN: 11.57 MIN: 11.64 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU B C A 1.1515 2.303 3.4545 4.606 5.7575 SE +/- 0.00391, N = 3 SE +/- 0.00500, N = 3 SE +/- 0.00093, N = 3 5.11311 5.11709 5.11790 MIN: 4.9 MIN: 4.92 MIN: 4.83 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU B C A 2 4 6 8 10 SE +/- 0.00293, N = 3 SE +/- 0.01365, N = 3 SE +/- 0.00982, N = 3 8.02814 8.03124 8.03215 MIN: 7.79 MIN: 7.55 MIN: 7.71 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU A C B 1000 2000 3000 4000 5000 SE +/- 13.87, N = 3 SE +/- 23.16, N = 3 SE +/- 11.37, N = 3 4688.21 4690.50 4690.55 MIN: 4643 MIN: 4623.54 MIN: 4647.66 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU C B A 9 18 27 36 45 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 2.09, N = 12 33.72 33.74 37.77 MIN: 33.44 MIN: 33.42 MIN: 33.4 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl -lpthread
Phoronix Test Suite v10.8.4