AMD Ryzen 7 4700U testing with a LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS) and AMD Renoir 512MB on Ubuntu 23.04 via the Phoronix Test Suite.
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --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-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/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 -vProcessor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balancedJava Notes: OpenJDK Runtime Environment (build 17.0.7+7-Ubuntu-0ubuntu123.04)Python Notes: Python 3.11.2Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT disabled + 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 STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
b Processor: AMD Ryzen 7 4700U @ 2.00GHz (8 Cores), Motherboard: LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 512GB SAMSUNG MZALQ512HALU-000L2, Graphics: AMD Renoir 512MB (1600/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Intel Wi-Fi 6 AX200
OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080
c OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --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-DAPbBt/gcc-12-12.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-DAPbBt/gcc-12-12.3.0/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 -vProcessor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balancedJava Notes: OpenJDK Runtime Environment (build 17.0.8.1+1-Ubuntu-0ubuntu123.04)Python Notes: Python 3.11.4Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT disabled + 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 STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
ss OpenBenchmarking.org Phoronix Test Suite AMD Ryzen 7 4700U @ 2.00GHz (8 Cores) LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS) AMD Renoir/Cezanne 16GB 512GB SAMSUNG MZALQ512HALU-000L2 AMD Renoir 512MB (1600/400MHz) AMD Renoir Radeon HD Audio Intel Wi-Fi 6 AX200 Ubuntu 23.04 6.2.0-24-generic (x86_64) GNOME Shell 44.2 X Server + Wayland 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49) GCC 12.2.0 GCC 12.3.0 ext4 1920x1080 Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Compilers File-System Screen Resolution Ss Performance System Logs - Transparent Huge Pages: madvise - a: --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-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/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 - b: --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-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/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 - c: --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-DAPbBt/gcc-12-12.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-DAPbBt/gcc-12-12.3.0/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 - Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balanced - a: OpenJDK Runtime Environment (build 17.0.7+7-Ubuntu-0ubuntu123.04) - b: OpenJDK Runtime Environment (build 17.0.7+7-Ubuntu-0ubuntu123.04) - c: OpenJDK Runtime Environment (build 17.0.8.1+1-Ubuntu-0ubuntu123.04) - a: Python 3.11.2 - b: Python 3.11.2 - c: Python 3.11.4 - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT disabled + 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 STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
a b c Result Overview Phoronix Test Suite 100% 101% 101% 102% 103% BRL-CAD SVT-AV1 libavif avifenc OpenVKL VVenC OpenRadioss OpenVINO NCNN oneDNN easyWave Embree Timed GCC Compilation Intel Open Image Denoise
ss build-gcc: Time To Compile openradioss: INIVOL and Fluid Structure Interaction Drop Container easywave: e2Asean Grid + BengkuluSept2007 Source - 2400 brl-cad: VGR Performance Metric openvkl: vklBenchmarkCPU ISPC openvkl: vklBenchmarkCPU Scalar openradioss: Bird Strike on Windshield openradioss: Rubber O-Ring Seal Installation easywave: e2Asean Grid + BengkuluSept2007 Source - 1200 openradioss: Bumper Beam avifenc: 0 vvenc: Bosphorus 4K - Fast oidn: RTLightmap.hdr.4096x4096 - CPU-Only openradioss: Cell Phone Drop Test embree: Pathtracer ISPC - Crown embree: Pathtracer ISPC - Asian Dragon Obj embree: Pathtracer - Crown embree: Pathtracer - Asian Dragon Obj ncnn: CPU - FastestDet ncnn: CPU - vision_transformer ncnn: CPU - regnety_400m ncnn: CPU - squeezenet_ssd ncnn: CPU - yolov4-tiny ncnn: CPU - resnet50 ncnn: CPU - alexnet ncnn: CPU - resnet18 ncnn: CPU - vgg16 ncnn: CPU - googlenet ncnn: CPU - blazeface ncnn: CPU - efficientnet-b0 ncnn: CPU - mnasnet ncnn: CPU - shufflenet-v2 ncnn: CPU-v3-v3 - mobilenet-v3 ncnn: CPU-v2-v2 - mobilenet-v2 ncnn: CPU - mobilenet embree: Pathtracer ISPC - Asian Dragon embree: Pathtracer - Asian Dragon oidn: RT.ldr_alb_nrm.3840x2160 - CPU-Only oidn: RT.hdr_alb_nrm.3840x2160 - CPU-Only avifenc: 2 vvenc: Bosphorus 4K - Faster svt-av1: Preset 4 - Bosphorus 4K onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU vvenc: Bosphorus 1080p - Fast openvino: Face Detection FP16 - CPU openvino: Face Detection FP16 - CPU openvino: Face Detection FP16-INT8 - CPU openvino: Face Detection FP16-INT8 - CPU openvino: Machine Translation EN To DE FP16 - CPU openvino: Machine Translation EN To DE FP16 - CPU openvino: Person Detection FP32 - CPU openvino: Person Detection FP32 - CPU openvino: Person Detection FP16 - CPU openvino: Person Detection FP16 - CPU openvino: Road Segmentation ADAS FP16-INT8 - CPU openvino: Road Segmentation ADAS FP16-INT8 - CPU openvino: Person Vehicle Bike Detection FP16 - CPU openvino: Person Vehicle Bike Detection FP16 - CPU openvino: Road Segmentation ADAS FP16 - CPU openvino: Road Segmentation ADAS FP16 - CPU openvino: Vehicle Detection FP16-INT8 - CPU openvino: Vehicle Detection FP16-INT8 - CPU openvino: Handwritten English Recognition FP16 - CPU openvino: Handwritten English Recognition FP16 - CPU openvino: Handwritten English Recognition FP16-INT8 - CPU openvino: Handwritten English Recognition FP16-INT8 - CPU openvino: Face Detection Retail FP16-INT8 - CPU openvino: Face Detection Retail FP16-INT8 - CPU openvino: Vehicle Detection FP16 - CPU openvino: Vehicle Detection FP16 - CPU openvino: Weld Porosity Detection FP16-INT8 - CPU openvino: Weld Porosity Detection FP16-INT8 - CPU openvino: Weld Porosity Detection FP16 - CPU openvino: Weld Porosity Detection FP16 - CPU openvino: Face Detection Retail FP16 - CPU openvino: Face Detection Retail FP16 - CPU openvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPU openvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPU openvino: Age Gender Recognition Retail 0013 FP16 - CPU openvino: Age Gender Recognition Retail 0013 FP16 - CPU svt-av1: Preset 8 - Bosphorus 4K vvenc: Bosphorus 1080p - Faster svt-av1: Preset 4 - Bosphorus 1080p easywave: e2Asean Grid + BengkuluSept2007 Source - 240 onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU avifenc: 6, Lossless svt-av1: Preset 12 - Bosphorus 4K onednn: IP Shapes 1D - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU svt-av1: Preset 13 - Bosphorus 4K avifenc: 6 svt-av1: Preset 8 - Bosphorus 1080p onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU avifenc: 10, Lossless onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU svt-av1: Preset 12 - Bosphorus 1080p onednn: Deconvolution Batch shapes_3d - f32 - CPU svt-av1: Preset 13 - Bosphorus 1080p onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: IP Shapes 3D - bf16bf16bf16 - CPU a b c 1991.499 1253.59 1073.635 81531 89 47 499.42 446.33 440.836 327.2 270.502 2.356 0.12 193.95 4.2922 4.6132 4.7585 5.1118 4.74 193.64 8.32 18.06 38.15 29.58 9.99 12.64 90.47 17.65 1.18 8.55 4.57 3.52 4.53 6.57 23.33 5.3249 5.6936 0.24 0.24 121.67 4.947 1.574 6737.34 6724.77 6461.79 4113.7 4149.54 4152.97 7.605 2569.23 1.55 1944.19 2.05 230.97 17.29 303.3 13.17 300.95 13.28 64.94 61.56 21.33 187.25 212.75 18.79 30.29 131.93 85.92 46.52 80.18 49.86 8.6 463.38 42.37 94.29 19.53 204.56 26.75 149.41 10.41 382.87 0.75 5097.25 1.49 2625.67 17.27 17.377 5.504 27.084 4.36329 7.45384 19.649 38.8 10.5425 3.42484 42.786 13.512 47.466 16.3623 3.4916 8.285 30.653 33.0526 172.623 10.4334 211.723 5.3054 1990.347 1249.12 1072.578 79432 89 47 497.06 446.63 441.137 329.4 270.156 2.348 0.12 194.05 4.2996 4.6139 4.7405 5.0954 4.68 194.64 8.48 18.49 38.26 29.14 9.98 12.68 90.72 17.67 1.19 8.65 4.54 3.55 4.58 6.5 23.67 5.3213 5.6994 0.24 0.24 123.495 4.907 1.56 6696.23 6686.99 6534.4 4095.25 4133.13 4145.96 7.622 2563.03 1.56 1940.1 2.06 235.81 16.95 295.24 13.55 295.93 13.51 64.98 61.5 20.97 190.52 211.66 18.88 30.39 131.51 85.32 46.84 82.02 48.73 8.6 462.94 42.59 93.82 19.53 204.54 26.53 150.6 10.28 387.95 0.75 5149.13 1.49 2616.41 17.254 17.341 5.382 27.12 4.35154 7.45289 20.329 38.68 10.5181 3.41832 42.285 13.537 45.571 16.3754 3.49591 8.333 30.6772 33.0297 169.671 10.7266 211.721 5.44214 1995.474 1253.9 1071.158 81055 89 46 494.53 445.43 440.479 323.25 272.77 2.345 0.12 193.29 4.2759 4.6097 4.749 5.1121 4.74 194.52 8.5 18.26 38.12 28.89 10.02 12.65 90.54 17.78 1.2 8.64 4.57 3.52 4.63 6.47 23.56 5.3375 5.6935 0.24 0.24 123.824 4.926 1.558 6703.84 6731.81 6523.04 4079.25 4145.86 4155.31 7.577 2552.54 1.56 1941.23 2.06 231.16 17.28 300.85 13.28 302.13 13.22 65.48 61.03 20.96 190.58 211.36 18.92 30.39 131.51 86.79 46.07 82.26 48.58 8.6 463.23 42.75 93.45 19.6 203.8 26.87 148.73 10.44 382.01 0.75 5162.26 1.49 2614.51 17.026 17.29 5.327 27.073 4.39631 7.54331 19.613 38.374 10.5025 3.43182 42.397 13.627 45.446 16.3467 3.48493 8.285 30.6843 33.0971 168.521 10.4516 210.311 5.35481 OpenBenchmarking.org
OpenRadioss OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better OpenRadioss 2023.09.15 Model: INIVOL and Fluid Structure Interaction Drop Container a b c 300 600 900 1200 1500 1253.59 1249.12 1253.90
easyWave The easyWave software allows simulating tsunami generation and propagation in the context of early warning systems. EasyWave supports making use of OpenMP for CPU multi-threading and there are also GPU ports available but not currently incorporated as part of this test profile. The easyWave tsunami generation software is run with one of the example/reference input files for measuring the CPU execution time. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 a b c 200 400 600 800 1000 1073.64 1072.58 1071.16 1. (CXX) g++ options: -O3 -fopenmp
BRL-CAD BRL-CAD is a cross-platform, open-source solid modeling system with built-in benchmark mode. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org VGR Performance Metric, More Is Better BRL-CAD 7.36 VGR Performance Metric a b c 20K 40K 60K 80K 100K 81531 79432 81055 1. (CXX) g++ options: -std=c++14 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lregex_brl -lz_brl -lnetpbm -ldl -lm -ltk8.6
OpenRadioss OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better OpenRadioss 2023.09.15 Model: Bird Strike on Windshield a b c 110 220 330 440 550 499.42 497.06 494.53
easyWave The easyWave software allows simulating tsunami generation and propagation in the context of early warning systems. EasyWave supports making use of OpenMP for CPU multi-threading and there are also GPU ports available but not currently incorporated as part of this test profile. The easyWave tsunami generation software is run with one of the example/reference input files for measuring the CPU execution time. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 a b c 100 200 300 400 500 440.84 441.14 440.48 1. (CXX) g++ options: -O3 -fopenmp
OpenRadioss OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better OpenRadioss 2023.09.15 Model: Bumper Beam a b c 70 140 210 280 350 327.20 329.40 323.25
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 4K - Video Preset: Fast a b c 0.5301 1.0602 1.5903 2.1204 2.6505 2.356 2.348 2.345 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
OpenRadioss OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better OpenRadioss 2023.09.15 Model: Cell Phone Drop Test a b c 40 80 120 160 200 193.95 194.05 193.29
Embree OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Crown a b c 0.9674 1.9348 2.9022 3.8696 4.837 4.2922 4.2996 4.2759 MIN: 4.27 / MAX: 4.33 MIN: 4.27 / MAX: 4.35 MIN: 4.26 / MAX: 4.32
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj a b c 1.0381 2.0762 3.1143 4.1524 5.1905 4.6132 4.6139 4.6097 MIN: 4.6 / MAX: 4.65 MIN: 4.6 / MAX: 4.66 MIN: 4.59 / MAX: 4.66
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer - Model: Crown a b c 1.0707 2.1414 3.2121 4.2828 5.3535 4.7585 4.7405 4.7490 MIN: 4.74 / MAX: 4.81 MIN: 4.72 / MAX: 4.8 MIN: 4.73 / MAX: 4.79
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj a b c 1.1502 2.3004 3.4506 4.6008 5.751 5.1118 5.0954 5.1121 MIN: 5.09 / MAX: 5.16 MIN: 5.08 / MAX: 5.15 MIN: 5.09 / MAX: 5.16
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: FastestDet a b c 1.0665 2.133 3.1995 4.266 5.3325 4.74 4.68 4.74 MIN: 4.69 / MAX: 5.22 MIN: 4.62 / MAX: 5.16 MIN: 4.68 / MAX: 5.3 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: vision_transformer a b c 40 80 120 160 200 193.64 194.64 194.52 MIN: 192.59 / MAX: 202.18 MIN: 193.96 / MAX: 228.43 MIN: 193.79 / MAX: 203.39 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: regnety_400m a b c 2 4 6 8 10 8.32 8.48 8.50 MIN: 8.16 / MAX: 9.77 MIN: 8.31 / MAX: 9.76 MIN: 8.34 / MAX: 9.82 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: squeezenet_ssd a b c 5 10 15 20 25 18.06 18.49 18.26 MIN: 17.71 / MAX: 20.14 MIN: 17.85 / MAX: 19.43 MIN: 17.82 / MAX: 19.17 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: yolov4-tiny a b c 9 18 27 36 45 38.15 38.26 38.12 MIN: 37.7 / MAX: 41.2 MIN: 37.87 / MAX: 46.83 MIN: 37.67 / MAX: 38.97 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: resnet50 a b c 7 14 21 28 35 29.58 29.14 28.89 MIN: 28.4 / MAX: 115.97 MIN: 28.67 / MAX: 38 MIN: 28.59 / MAX: 29.78 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: alexnet a b c 3 6 9 12 15 9.99 9.98 10.02 MIN: 9.84 / MAX: 11.09 MIN: 9.81 / MAX: 11.32 MIN: 9.88 / MAX: 11.43 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: resnet18 a b c 3 6 9 12 15 12.64 12.68 12.65 MIN: 12.43 / MAX: 14.45 MIN: 12.52 / MAX: 14.32 MIN: 12.48 / MAX: 14.77 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: vgg16 a b c 20 40 60 80 100 90.47 90.72 90.54 MIN: 89.96 / MAX: 98.67 MIN: 90.13 / MAX: 99.74 MIN: 89.98 / MAX: 100.81 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: googlenet a b c 4 8 12 16 20 17.65 17.67 17.78 MIN: 17.27 / MAX: 19.24 MIN: 17.22 / MAX: 25.89 MIN: 17.33 / MAX: 20.39 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: blazeface a b c 0.27 0.54 0.81 1.08 1.35 1.18 1.19 1.20 MIN: 1.15 / MAX: 1.31 MIN: 1.14 / MAX: 2.05 MIN: 1.16 / MAX: 1.89 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: efficientnet-b0 a b c 2 4 6 8 10 8.55 8.65 8.64 MIN: 8.36 / MAX: 16.45 MIN: 8.49 / MAX: 10.28 MIN: 8.52 / MAX: 10.13 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: mnasnet a b c 1.0283 2.0566 3.0849 4.1132 5.1415 4.57 4.54 4.57 MIN: 4.46 / MAX: 5.89 MIN: 4.44 / MAX: 5.81 MIN: 4.49 / MAX: 6.07 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: shufflenet-v2 a b c 0.7988 1.5976 2.3964 3.1952 3.994 3.52 3.55 3.52 MIN: 3.45 / MAX: 4.33 MIN: 3.49 / MAX: 4.42 MIN: 3.46 / MAX: 4.76 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU-v3-v3 - Model: mobilenet-v3 a b c 1.0418 2.0836 3.1254 4.1672 5.209 4.53 4.58 4.63 MIN: 4.43 / MAX: 5.84 MIN: 4.44 / MAX: 6.01 MIN: 4.48 / MAX: 6.44 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU-v2-v2 - Model: mobilenet-v2 a b c 2 4 6 8 10 6.57 6.50 6.47 MIN: 6.35 / MAX: 7.94 MIN: 6.29 / MAX: 15.2 MIN: 6.28 / MAX: 7.43 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: mobilenet a b c 6 12 18 24 30 23.33 23.67 23.56 MIN: 22.94 / MAX: 31.66 MIN: 23.24 / MAX: 31.55 MIN: 23.13 / MAX: 25.79 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Embree OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon a b c 1.2009 2.4018 3.6027 4.8036 6.0045 5.3249 5.3213 5.3375 MIN: 5.31 / MAX: 5.38 MIN: 5.3 / MAX: 5.38 MIN: 5.32 / MAX: 5.38
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer - Model: Asian Dragon a b c 1.2824 2.5648 3.8472 5.1296 6.412 5.6936 5.6994 5.6935 MIN: 5.67 / MAX: 5.75 MIN: 5.68 / MAX: 5.76 MIN: 5.67 / MAX: 5.74
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 4K - Video Preset: Faster a b c 1.1131 2.2262 3.3393 4.4524 5.5655 4.947 4.907 4.926 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 4K a b c 0.3542 0.7084 1.0626 1.4168 1.771 1.574 1.560 1.558 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU a b c 1400 2800 4200 5600 7000 6737.34 6696.23 6703.84 MIN: 6702.31 MIN: 6662.07 MIN: 6668.77 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU a b c 1400 2800 4200 5600 7000 6724.77 6686.99 6731.81 MIN: 6697.44 MIN: 6654.65 MIN: 6695.64 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU a b c 1400 2800 4200 5600 7000 6461.79 6534.40 6523.04 MIN: 6406.51 MIN: 6472.29 MIN: 6457.15 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU a b c 900 1800 2700 3600 4500 4113.70 4095.25 4079.25 MIN: 4070.68 MIN: 4059.62 MIN: 4040.34 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU a b c 900 1800 2700 3600 4500 4149.54 4133.13 4145.86 MIN: 4116.1 MIN: 4094.47 MIN: 4107.56 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU a b c 900 1800 2700 3600 4500 4152.97 4145.96 4155.31 MIN: 4116.58 MIN: 4110 MIN: 4118.92 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 1080p - Video Preset: Fast a b c 2 4 6 8 10 7.605 7.622 7.577 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
OpenVINO OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Face Detection FP16 - Device: CPU a b c 600 1200 1800 2400 3000 2569.23 2563.03 2552.54 MIN: 2507.71 / MAX: 2629.27 MIN: 2500.02 / MAX: 2625.07 MIN: 2468.86 / MAX: 2667.96 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Face Detection FP16 - Device: CPU a b c 0.351 0.702 1.053 1.404 1.755 1.55 1.56 1.56 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Face Detection FP16-INT8 - Device: CPU a b c 400 800 1200 1600 2000 1944.19 1940.10 1941.23 MIN: 1885.71 / MAX: 1969.4 MIN: 1881.22 / MAX: 1969.48 MIN: 1871.92 / MAX: 1958.1 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Face Detection FP16-INT8 - Device: CPU a b c 0.4635 0.927 1.3905 1.854 2.3175 2.05 2.06 2.06 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Machine Translation EN To DE FP16 - Device: CPU a b c 50 100 150 200 250 230.97 235.81 231.16 MIN: 160.47 / MAX: 259.14 MIN: 185.64 / MAX: 265.48 MIN: 180.68 / MAX: 265.27 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Machine Translation EN To DE FP16 - Device: CPU a b c 4 8 12 16 20 17.29 16.95 17.28 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Person Detection FP32 - Device: CPU a b c 70 140 210 280 350 303.30 295.24 300.85 MIN: 194.13 / MAX: 337.4 MIN: 260.56 / MAX: 327.23 MIN: 246.14 / MAX: 323.82 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Person Detection FP32 - Device: CPU a b c 3 6 9 12 15 13.17 13.55 13.28 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Person Detection FP16 - Device: CPU a b c 70 140 210 280 350 300.95 295.93 302.13 MIN: 212.47 / MAX: 325.32 MIN: 261.78 / MAX: 327.58 MIN: 203.75 / MAX: 324.79 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Person Detection FP16 - Device: CPU a b c 3 6 9 12 15 13.28 13.51 13.22 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Road Segmentation ADAS FP16-INT8 - Device: CPU a b c 15 30 45 60 75 64.94 64.98 65.48 MIN: 48.91 / MAX: 89.37 MIN: 41.15 / MAX: 98.79 MIN: 44.92 / MAX: 95.54 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Road Segmentation ADAS FP16-INT8 - Device: CPU a b c 14 28 42 56 70 61.56 61.50 61.03 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Person Vehicle Bike Detection FP16 - Device: CPU a b c 5 10 15 20 25 21.33 20.97 20.96 MIN: 13.65 / MAX: 41.01 MIN: 17.73 / MAX: 34.13 MIN: 16.75 / MAX: 35.05 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Person Vehicle Bike Detection FP16 - Device: CPU a b c 40 80 120 160 200 187.25 190.52 190.58 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Road Segmentation ADAS FP16 - Device: CPU a b c 50 100 150 200 250 212.75 211.66 211.36 MIN: 96.01 / MAX: 240.84 MIN: 123.15 / MAX: 247.61 MIN: 176.61 / MAX: 241.25 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Road Segmentation ADAS FP16 - Device: CPU a b c 5 10 15 20 25 18.79 18.88 18.92 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Vehicle Detection FP16-INT8 - Device: CPU a b c 7 14 21 28 35 30.29 30.39 30.39 MIN: 19.37 / MAX: 50.54 MIN: 22.38 / MAX: 63.1 MIN: 19.84 / MAX: 56.56 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Vehicle Detection FP16-INT8 - Device: CPU a b c 30 60 90 120 150 131.93 131.51 131.51 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Handwritten English Recognition FP16 - Device: CPU a b c 20 40 60 80 100 85.92 85.32 86.79 MIN: 64.99 / MAX: 113.89 MIN: 60.39 / MAX: 115.66 MIN: 68.17 / MAX: 106.82 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Handwritten English Recognition FP16 - Device: CPU a b c 11 22 33 44 55 46.52 46.84 46.07 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Handwritten English Recognition FP16-INT8 - Device: CPU a b c 20 40 60 80 100 80.18 82.02 82.26 MIN: 56.84 / MAX: 111.31 MIN: 60.11 / MAX: 105.01 MIN: 54.73 / MAX: 109.61 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Handwritten English Recognition FP16-INT8 - Device: CPU a b c 11 22 33 44 55 49.86 48.73 48.58 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Face Detection Retail FP16-INT8 - Device: CPU a b c 2 4 6 8 10 8.6 8.6 8.6 MIN: 6.16 / MAX: 18.26 MIN: 6.19 / MAX: 21.79 MIN: 6.18 / MAX: 18.51 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Face Detection Retail FP16-INT8 - Device: CPU a b c 100 200 300 400 500 463.38 462.94 463.23 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Vehicle Detection FP16 - Device: CPU a b c 10 20 30 40 50 42.37 42.59 42.75 MIN: 24.69 / MAX: 62.44 MIN: 31.36 / MAX: 60.83 MIN: 26.04 / MAX: 60.31 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Vehicle Detection FP16 - Device: CPU a b c 20 40 60 80 100 94.29 93.82 93.45 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Weld Porosity Detection FP16-INT8 - Device: CPU a b c 5 10 15 20 25 19.53 19.53 19.60 MIN: 14.45 / MAX: 37.23 MIN: 14.42 / MAX: 33.59 MIN: 14.38 / MAX: 34.49 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Weld Porosity Detection FP16-INT8 - Device: CPU a b c 40 80 120 160 200 204.56 204.54 203.80 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Weld Porosity Detection FP16 - Device: CPU a b c 6 12 18 24 30 26.75 26.53 26.87 MIN: 20.55 / MAX: 37.44 MIN: 20.36 / MAX: 38.12 MIN: 20.33 / MAX: 43.94 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Weld Porosity Detection FP16 - Device: CPU a b c 30 60 90 120 150 149.41 150.60 148.73 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Face Detection Retail FP16 - Device: CPU a b c 3 6 9 12 15 10.41 10.28 10.44 MIN: 8.3 / MAX: 26.03 MIN: 7.77 / MAX: 27.86 MIN: 8.31 / MAX: 26.72 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Face Detection Retail FP16 - Device: CPU a b c 80 160 240 320 400 382.87 387.95 382.01 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU a b c 0.1688 0.3376 0.5064 0.6752 0.844 0.75 0.75 0.75 MIN: 0.52 / MAX: 12.69 MIN: 0.52 / MAX: 11.08 MIN: 0.52 / MAX: 11.78 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU a b c 1100 2200 3300 4400 5500 5097.25 5149.13 5162.26 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU a b c 0.3353 0.6706 1.0059 1.3412 1.6765 1.49 1.49 1.49 MIN: 1.03 / MAX: 16.09 MIN: 0.98 / MAX: 18.34 MIN: 1.13 / MAX: 19.2 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU a b c 600 1200 1800 2400 3000 2625.67 2616.41 2614.51 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 4K a b c 4 8 12 16 20 17.27 17.25 17.03 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
VVenC VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better VVenC 1.9 Video Input: Bosphorus 1080p - Video Preset: Faster a b c 4 8 12 16 20 17.38 17.34 17.29 1. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 1080p a b c 1.2384 2.4768 3.7152 4.9536 6.192 5.504 5.382 5.327 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
easyWave The easyWave software allows simulating tsunami generation and propagation in the context of early warning systems. EasyWave supports making use of OpenMP for CPU multi-threading and there are also GPU ports available but not currently incorporated as part of this test profile. The easyWave tsunami generation software is run with one of the example/reference input files for measuring the CPU execution time. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 a b c 6 12 18 24 30 27.08 27.12 27.07 1. (CXX) g++ options: -O3 -fopenmp
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU a b c 0.9892 1.9784 2.9676 3.9568 4.946 4.36329 4.35154 4.39631 MIN: 3.95 MIN: 4.04 MIN: 4.07 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU a b c 2 4 6 8 10 7.45384 7.45289 7.54331 MIN: 6.49 MIN: 6.46 MIN: 6.35 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 4K a b c 9 18 27 36 45 38.80 38.68 38.37 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU a b c 3 6 9 12 15 10.54 10.52 10.50 MIN: 10.06 MIN: 10.06 MIN: 9.99 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU a b c 0.7722 1.5444 2.3166 3.0888 3.861 3.42484 3.41832 3.43182 MIN: 3.26 MIN: 3.11 MIN: 3.23 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 4K a b c 10 20 30 40 50 42.79 42.29 42.40 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 1080p a b c 11 22 33 44 55 47.47 45.57 45.45 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU a b c 4 8 12 16 20 16.36 16.38 16.35 MIN: 15.38 MIN: 15.65 MIN: 15.62 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU a b c 0.7866 1.5732 2.3598 3.1464 3.933 3.49160 3.49591 3.48493 MIN: 3.41 MIN: 3.43 MIN: 3.41 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU a b c 7 14 21 28 35 30.65 30.68 30.68 MIN: 30.44 MIN: 30.51 MIN: 30.43 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU a b c 8 16 24 32 40 33.05 33.03 33.10 MIN: 32.33 MIN: 32.6 MIN: 32.64 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 1080p a b c 40 80 120 160 200 172.62 169.67 168.52 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU a b c 3 6 9 12 15 10.43 10.73 10.45 MIN: 9.58 MIN: 9.4 MIN: 9.17 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
SVT-AV1 OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 1080p a b c 50 100 150 200 250 211.72 211.72 210.31 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU a b c 1.2245 2.449 3.6735 4.898 6.1225 5.30540 5.44214 5.35481 MIN: 4.89 MIN: 4.97 MIN: 4.83 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
Apache Cassandra This is a benchmark of the Apache Cassandra NoSQL database management system making use of cassandra-stress. Learn more via the OpenBenchmarking.org test page.
Test: Writes
a: The test run did not produce a result.
b: The test run did not produce a result.
c: The test run did not produce a result.
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
a: The test run did not produce a result.
b: The test run did not produce a result.
c: The test run did not produce a result.
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
a: The test run did not produce a result.
b: The test run did not produce a result.
c: The test run did not produce a result.
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
a: The test run did not produce a result.
b: The test run did not produce a result.
c: The test run did not produce a result.
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
a: The test run did not produce a result.
b: The test run did not produce a result.
c: The test run did not produce a result.
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
a: The test run did not produce a result.
b: The test run did not produce a result.
c: The test run did not produce a result.
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --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-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/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 -vProcessor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balancedJava Notes: OpenJDK Runtime Environment (build 17.0.7+7-Ubuntu-0ubuntu123.04)Python Notes: Python 3.11.2Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT disabled + 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 STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 18 October 2023 20:51 by user phoronix.
b Processor: AMD Ryzen 7 4700U @ 2.00GHz (8 Cores), Motherboard: LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 512GB SAMSUNG MZALQ512HALU-000L2, Graphics: AMD Renoir 512MB (1600/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Intel Wi-Fi 6 AX200
OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --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-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/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 -vProcessor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balancedJava Notes: OpenJDK Runtime Environment (build 17.0.7+7-Ubuntu-0ubuntu123.04)Python Notes: Python 3.11.2Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT disabled + 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 STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 19 October 2023 00:57 by user phoronix.
c Processor: AMD Ryzen 7 4700U @ 2.00GHz (8 Cores), Motherboard: LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: 512GB SAMSUNG MZALQ512HALU-000L2, Graphics: AMD Renoir 512MB (1600/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Intel Wi-Fi 6 AX200
OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --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-DAPbBt/gcc-12-12.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-DAPbBt/gcc-12-12.3.0/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 -vProcessor Notes: Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balancedJava Notes: OpenJDK Runtime Environment (build 17.0.8.1+1-Ubuntu-0ubuntu123.04)Python Notes: Python 3.11.4Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT disabled + 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 STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 19 October 2023 10:01 by user phoronix.