Intel Core i5-1145G7 testing with a LENOVO 20XW004AUS (N32ET71W 1.47 BIOS) and Intel Xe TGL GT2 3GB on Ubuntu 20.04 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 2203301-NE-ONEDNNTGL27 onednn tgl - Phoronix Test Suite onednn tgl Intel Core i5-1145G7 testing with a LENOVO 20XW004AUS (N32ET71W 1.47 BIOS) and Intel Xe TGL GT2 3GB on Ubuntu 20.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2203301-NE-ONEDNNTGL27&grs&rdt .
onednn tgl Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution A B C Intel Core i5-1145G7 @ 4.40GHz (4 Cores / 8 Threads) LENOVO 20XW004AUS (N32ET71W 1.47 BIOS) Intel Device a0ef 16GB 1024GB SAMSUNG MZVLB1T0HBLR-000H1 Intel Xe TGL GT2 3GB (1300MHz) Realtek ALC287 Intel Device a0f0 Ubuntu 20.04 5.14.0-1027-oem (x86_64) GNOME Shell 3.36.9 X Server 1.20.13 4.6 Mesa 21.2.6 1.2.182 GCC 9.4.0 ext4 1920x1200 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-yTrUTS/gcc-9-9.4.0/debian/tmp-nvptx/usr,hsa --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: intel_pstate powersave (EPP: balance_performance) - Platform Profile: balanced - CPU Microcode: 0x88 - ACPI Profile: balanced Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
onednn tgl onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: IP Shapes 3D - bf16bf16bf16 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: IP Shapes 3D - f32 - CPU onednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPU onednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: IP Shapes 1D - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - bf16bf16bf16 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: IP Shapes 1D - f32 - CPU A B C 7.00896 2.11018 6.11673 10.1712 2.41032 5.40966 38.2692 38.0359 4767.33 19.8379 4760.20 9343.97 9344.99 9342.56 4762.61 12.27494 1.70174 3.97598 63.5556 3.00906 17.6982 9.41308 1.95301 8.46208 7.61626 2.28842 6.31136 9.9306 2.35766 5.40629 38.3114 37.9739 4768.46 19.8353 4762.01 9342.43 9347.91 9340.03 4762.94 12.19882 1.70897 3.97577 63.9284 3.03781 18.3013 9.99736 2.08277 8.95669 7.63750 2.29786 6.35160 9.82487 2.34011 5.45216 38.3988 37.9609 4759.63 19.8015 4764.79 9341.05 9346.82 9341.19 4763.90 12.20369 1.71077 3.98095 64.4608 3.07591 18.2109 10.51531 2.16909 9.51734 OpenBenchmarking.org
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 A B C 2 4 6 8 10 SE +/- 0.03577, N = 3 SE +/- 0.09598, N = 12 SE +/- 0.07577, N = 15 7.00896 7.61626 7.63750 MIN: 6.9 MIN: 6.9 MIN: 6.9 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 0.517 1.034 1.551 2.068 2.585 SE +/- 0.01978, N = 3 SE +/- 0.02070, N = 15 SE +/- 0.02260, N = 14 2.11018 2.28842 2.29786 MIN: 2.05 MIN: 2.05 MIN: 2.05 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
oneDNN Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU A B C 2 4 6 8 10 SE +/- 0.04671, N = 15 SE +/- 0.06459, N = 15 SE +/- 0.08757, N = 12 6.11673 6.31136 6.35160 MIN: 4.83 MIN: 4.78 MIN: 4.8 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 3 6 9 12 15 SE +/- 0.07037, N = 3 SE +/- 0.05241, N = 3 SE +/- 0.01380, N = 3 10.17120 9.93060 9.82487 MIN: 9.72 MIN: 9.72 MIN: 9.72 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 0.5423 1.0846 1.6269 2.1692 2.7115 SE +/- 0.01651, N = 3 SE +/- 0.01602, N = 3 SE +/- 0.01606, N = 3 2.41032 2.35766 2.34011 MIN: 2.26 MIN: 2.26 MIN: 2.26 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 1.2267 2.4534 3.6801 4.9068 6.1335 SE +/- 0.01720, N = 3 SE +/- 0.02326, N = 3 SE +/- 0.05103, N = 3 5.40966 5.40629 5.45216 MIN: 5.31 MIN: 5.3 MIN: 5.3 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU A B C 9 18 27 36 45 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.06, N = 3 38.27 38.31 38.40 MIN: 38.12 MIN: 38.14 MIN: 38.12 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU A B C 9 18 27 36 45 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 38.04 37.97 37.96 MIN: 37.87 MIN: 37.88 MIN: 37.88 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 B C 1000 2000 3000 4000 5000 SE +/- 10.55, N = 3 SE +/- 7.12, N = 3 SE +/- 5.52, N = 3 4767.33 4768.46 4759.63 MIN: 4703.91 MIN: 4712.04 MIN: 4706.4 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
oneDNN Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU A B C 5 10 15 20 25 SE +/- 0.18, N = 7 SE +/- 0.18, N = 7 SE +/- 0.18, N = 7 19.84 19.84 19.80 MIN: 18.31 MIN: 18.36 MIN: 18.39 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 1000 2000 3000 4000 5000 SE +/- 4.70, N = 3 SE +/- 5.86, N = 3 SE +/- 9.20, N = 3 4760.20 4762.01 4764.79 MIN: 4708.81 MIN: 4707.88 MIN: 4707.42 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 2K 4K 6K 8K 10K SE +/- 15.58, N = 3 SE +/- 13.80, N = 3 SE +/- 11.27, N = 3 9343.97 9342.43 9341.05 MIN: 9275.54 MIN: 9281.9 MIN: 9283.35 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 2K 4K 6K 8K 10K SE +/- 14.60, N = 3 SE +/- 10.74, N = 3 SE +/- 14.63, N = 3 9344.99 9347.91 9346.82 MIN: 9276.29 MIN: 9286.78 MIN: 9277.56 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 2K 4K 6K 8K 10K SE +/- 7.36, N = 3 SE +/- 13.01, N = 3 SE +/- 16.10, N = 3 9342.56 9340.03 9341.19 MIN: 9290.71 MIN: 9275.58 MIN: 9269.09 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 1000 2000 3000 4000 5000 SE +/- 9.66, N = 3 SE +/- 4.91, N = 3 SE +/- 8.66, N = 3 4762.61 4762.94 4763.90 MIN: 4701.82 MIN: 4712.41 MIN: 4704.67 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU A B C 3 6 9 12 15 SE +/- 0.38, N = 12 SE +/- 0.35, N = 12 SE +/- 0.35, N = 12 12.27 12.20 12.20 MIN: 7.73 MIN: 7.72 MIN: 7.72 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 0.3849 0.7698 1.1547 1.5396 1.9245 SE +/- 0.03407, N = 12 SE +/- 0.03087, N = 12 SE +/- 0.02902, N = 12 1.70174 1.70897 1.71077 MIN: 1.2 MIN: 1.19 MIN: 1.2 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 0.8957 1.7914 2.6871 3.5828 4.4785 SE +/- 0.10299, N = 12 SE +/- 0.08596, N = 12 SE +/- 0.08379, N = 12 3.97598 3.97577 3.98095 MIN: 2.51 MIN: 2.5 MIN: 2.5 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU A B C 14 28 42 56 70 SE +/- 1.13, N = 12 SE +/- 1.15, N = 12 SE +/- 1.22, N = 12 63.56 63.93 64.46 MIN: 48.57 MIN: 48.09 MIN: 48.75 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 0.6921 1.3842 2.0763 2.7684 3.4605 SE +/- 0.06611, N = 12 SE +/- 0.06747, N = 12 SE +/- 0.07382, N = 12 3.00906 3.03781 3.07591 MIN: 1.98 MIN: 1.99 MIN: 1.97 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 5 10 15 20 25 SE +/- 0.31, N = 12 SE +/- 0.37, N = 15 SE +/- 0.43, N = 12 17.70 18.30 18.21 MIN: 12.6 MIN: 12.66 MIN: 12.85 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 3 6 9 12 15 SE +/- 0.13110, N = 15 SE +/- 0.20633, N = 15 SE +/- 0.26927, N = 15 9.41308 9.99736 10.51531 MIN: 7.82 MIN: 7.8 MIN: 7.8 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 B C 0.488 0.976 1.464 1.952 2.44 SE +/- 0.02279, N = 15 SE +/- 0.03381, N = 14 SE +/- 0.03939, N = 13 1.95301 2.08277 2.16909 MIN: 1.53 MIN: 1.42 MIN: 1.44 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
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 A B C 3 6 9 12 15 SE +/- 0.12800, N = 12 SE +/- 0.18359, N = 12 SE +/- 0.22405, N = 12 8.46208 8.95669 9.51734 MIN: 6.9 MIN: 6.78 MIN: 6.54 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -lpthread -ldl
Phoronix Test Suite v10.8.4