AMD Ryzen 7 PRO 6850U testing with a LENOVO 21CM0001US (R22ET51W 1.21 BIOS) and AMD Radeon 680M 1GB 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 2304019-NE-NN400873086 nn - Phoronix Test Suite nn AMD Ryzen 7 PRO 6850U testing with a LENOVO 21CM0001US (R22ET51W 1.21 BIOS) and AMD Radeon 680M 1GB on Ubuntu 22.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2304019-NE-NN400873086&sor&grr .
nn 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 7 PRO 6850U @ 4.77GHz (8 Cores / 16 Threads) LENOVO 21CM0001US (R22ET51W 1.21 BIOS) AMD Device 14b5 16GB 512GB Micron MTFDKBA512TFK AMD Radeon 680M 1GB (2200/400MHz) AMD Rembrandt Radeon HD Audio Qualcomm QCNFA765 Ubuntu 22.10 6.1.0-060100rc2daily20221028-generic (x86_64) GNOME Shell 43.0 X Server + Wayland 4.6 Mesa 22.2.1 (LLVM 15.0.2 DRM 3.49) 1.3.224 GCC 12.2.0 ext4 1920x1200 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: amd-pstate schedutil (Boost: Enabled) - Platform Profile: performance - CPU Microcode: 0xa404102 - ACPI Profile: performance 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
nn onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: IP Shapes 1D - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU a b c 4562.58 4553.89 4552.91 2469.2 2463.56 2474.1 2.56495 10.0031 4.36941 1.81578 8.18086 2.02698 12.2287 13.1213 8.07694 3.67848 4551.69 4551.98 4548.71 2457.66 2465.80 2459.02 2.74096 10.3179 4.44437 1.83971 8.12368 2.03008 12.1595 13.0792 8.12685 3.79923 4536.48 4548.35 4551.57 2464.31 2460.9 2458.21 2.55744 9.75495 4.35797 1.80262 8.13103 2.02174 12.227 13.0365 8.08516 3.68672 OpenBenchmarking.org
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU c b a 1000 2000 3000 4000 5000 SE +/- 9.14, N = 3 4536.48 4551.69 4562.58 MIN: 4416.52 MIN: 4424.71 MIN: 4445.92 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU c b a 1000 2000 3000 4000 5000 SE +/- 2.11, N = 3 4548.35 4551.98 4553.89 MIN: 4428.08 MIN: 4413.68 MIN: 4425 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU b c a 1000 2000 3000 4000 5000 SE +/- 2.22, N = 3 4548.71 4551.57 4552.91 MIN: 4435.72 MIN: 4425.76 MIN: 4433.05 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU b c a 500 1000 1500 2000 2500 SE +/- 4.71, N = 3 2457.66 2464.31 2469.20 MIN: 2347.78 MIN: 2364.84 MIN: 2365.36 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU c a b 500 1000 1500 2000 2500 SE +/- 8.86, N = 3 2460.90 2463.56 2465.80 MIN: 2352.41 MIN: 2370.88 MIN: 2358.31 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU c b a 500 1000 1500 2000 2500 SE +/- 5.36, N = 3 2458.21 2459.02 2474.10 MIN: 2362.82 MIN: 2350.09 MIN: 2373 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU c a b 0.6167 1.2334 1.8501 2.4668 3.0835 SE +/- 0.02745, N = 6 2.55744 2.56495 2.74096 MIN: 1.97 MIN: 1.94 MIN: 1.98 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU c a b 3 6 9 12 15 SE +/- 0.13209, N = 3 9.75495 10.00310 10.31790 MIN: 6.22 MIN: 5.87 MIN: 6.14 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU c a b 1 2 3 4 5 SE +/- 0.02097, N = 3 4.35797 4.36941 4.44437 MIN: 3.88 MIN: 3.85 MIN: 3.81 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU c a b 0.4139 0.8278 1.2417 1.6556 2.0695 SE +/- 0.00880, N = 3 1.80262 1.81578 1.83971 MIN: 1.36 MIN: 1.48 MIN: 1.39 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU b c a 2 4 6 8 10 SE +/- 0.00932, N = 3 8.12368 8.13103 8.18086 MIN: 7.92 MIN: 7.99 MIN: 8.02 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU c a b 0.4568 0.9136 1.3704 1.8272 2.284 SE +/- 0.00545, N = 3 2.02174 2.02698 2.03008 MIN: 1.87 MIN: 1.87 MIN: 1.85 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU b c a 3 6 9 12 15 SE +/- 0.04, N = 3 12.16 12.23 12.23 MIN: 11.88 MIN: 11.9 MIN: 11.95 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU c b a 3 6 9 12 15 SE +/- 0.01, N = 3 13.04 13.08 13.12 MIN: 12.75 MIN: 12.75 MIN: 12.77 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU a c b 2 4 6 8 10 SE +/- 0.01261, N = 3 8.07694 8.08516 8.12685 MIN: 7.77 MIN: 7.77 MIN: 7.71 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU a c b 0.8548 1.7096 2.5644 3.4192 4.274 SE +/- 0.02269, N = 3 3.67848 3.68672 3.79923 MIN: 3.37 MIN: 3.59 MIN: 3.53 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
Phoronix Test Suite v10.8.4