Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and llvmpipe on Ubuntu 22.04 via the Phoronix Test Suite.
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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 -vProcessor Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0x5003604Python Notes: Python 3.10.12Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Mitigation of Enhanced IBRS + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Mitigation of TSX disabled
b Processor: Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads), Motherboard: ASRock X299 Steel Legend (P1.30 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 32GB, Disk: Samsung SSD 970 PRO 512GB, Graphics: llvmpipe, Audio: Realtek ALC1220, Network: Intel I219-V + Intel I211
OS: Ubuntu 22.04, Kernel: 6.2.0-33-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server 1.21.1.3, OpenGL: 4.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits), Vulkan: 1.2.204, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 1024x768
aug OpenBenchmarking.org Phoronix Test Suite Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads) ASRock X299 Steel Legend (P1.30 BIOS) Intel Sky Lake-E DMI3 Registers 32GB Samsung SSD 970 PRO 512GB llvmpipe Realtek ALC1220 Intel I219-V + Intel I211 Ubuntu 22.04 6.2.0-33-generic (x86_64) GNOME Shell 42.2 X Server 1.21.1.3 4.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits) 1.2.204 GCC 11.4.0 ext4 1024x768 Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution Aug Benchmarks System Logs - Transparent Huge Pages: madvise - --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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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 - Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0x5003604 - Python 3.10.12 - gather_data_sampling: Mitigation of Microcode + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Mitigation of Enhanced IBRS + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Mitigation of TSX disabled
a vs. b Comparison Phoronix Test Suite Baseline +9.6% +9.6% +19.2% +19.2% +28.8% +28.8% 7% 6.7% 4.9% 3% 2.6% 2.6% 2.1% H.E.R.F.I - CPU 38.4% H.E.R.F.I - CPU 38.4% blosclz shuffle - 8MB 9% IP Shapes 1D - u8s8f32 - CPU H4_ae R.N.N.I - f32 - CPU r2c - FFTW - double - 256 3.2% r2c - FFTW - double - 128 IP Shapes 3D - u8s8f32 - CPU 2.9% R.N.N.T - f32 - CPU IP Shapes 3D - f32 - CPU R.N.N.I - bf16bf16bf16 - CPU 2.5% c2c - FFTW - float - 128 2.5% RTLightmap.hdr.4096x4096 - CPU-Only 2.4% IP Shapes 3D - bf16bf16bf16 - CPU OpenVINO OpenVINO C-Blosc oneDNN QMCPACK oneDNN HeFFTe - Highly Efficient FFT for Exascale HeFFTe - Highly Efficient FFT for Exascale oneDNN oneDNN oneDNN oneDNN HeFFTe - Highly Efficient FFT for Exascale Intel Open Image Denoise oneDNN a b
QuantLib QuantLib is an open-source library/framework around quantitative finance for modeling, trading and risk management scenarios. QuantLib is written in C++ with Boost and its built-in benchmark used reports the QuantLib Benchmark Index benchmark score. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.32 Configuration: Multi-Threaded b a 10K 20K 30K 40K 50K 44888.6 44641.0 1. (CXX) g++ options: -O3 -march=native -fPIE -pie
OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.32 Configuration: Single-Threaded b a 600 1200 1800 2400 3000 2684.2 2682.0 1. (CXX) g++ options: -O3 -march=native -fPIE -pie
OpenBenchmarking.org Seconds, Fewer Is Better CloverLeaf 1.3 Input: clover_bm64_short b a 50 100 150 200 250 211.67 212.72 1. (F9X) gfortran options: -O3 -march=native -funroll-loops -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: IP Shapes 1D - Data Type: f32 - Engine: CPU a b 0.5617 1.1234 1.6851 2.2468 2.8085 2.49348 2.49628 MIN: 2.28 MIN: 2.3 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: f32 - Engine: CPU b a 1.2124 2.4248 3.6372 4.8496 6.062 5.25114 5.38829 MIN: 5.21 MIN: 5.26 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 b a 0.1392 0.2784 0.4176 0.5568 0.696 0.578244 0.618773 MIN: 0.52 MIN: 0.53 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 0.2792 0.5584 0.8376 1.1168 1.396 1.20555 1.24078 MIN: 1.16 MIN: 1.15 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: bf16bf16bf16 - Engine: CPU a b 1.2469 2.4938 3.7407 4.9876 6.2345 5.49542 5.54192 MIN: 5.42 MIN: 5.37 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: bf16bf16bf16 - Engine: CPU b a 0.656 1.312 1.968 2.624 3.28 2.85512 2.91534 MIN: 2.58 MIN: 2.6 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 3 6 9 12 15 9.87746 9.88829 MIN: 9.8 MIN: 9.8 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 b a 2 4 6 8 10 6.86291 6.90110 MIN: 3.23 MIN: 3.2 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_3d - Data Type: f32 - Engine: CPU b a 0.6085 1.217 1.8255 2.434 3.0425 2.69575 2.70456 MIN: 2.67 MIN: 2.66 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: u8s8f32 - Engine: CPU a b 3 6 9 12 15 9.03440 9.05479 MIN: 8.95 MIN: 8.97 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: u8s8f32 - Engine: CPU b a 0.1183 0.2366 0.3549 0.4732 0.5915 0.525029 0.525652 MIN: 0.51 MIN: 0.51 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_3d - Data Type: u8s8f32 - Engine: CPU a b 0.1448 0.2896 0.4344 0.5792 0.724 0.633996 0.643669 MIN: 0.63 MIN: 0.6 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: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU b a 400 800 1200 1600 2000 1677.89 1722.09 MIN: 1648.93 MIN: 1656.78 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: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU b a 200 400 600 800 1000 898.31 941.96 MIN: 891.27 MIN: 908.05 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: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU a b 300 600 900 1200 1500 1615.72 1625.41 MIN: 1610.41 MIN: 1616.47 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: bf16bf16bf16 - Engine: CPU a b 2 4 6 8 10 7.85872 7.86557 MIN: 7.66 MIN: 7.67 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: bf16bf16bf16 - Engine: CPU b a 3 6 9 12 15 11.02 11.06 MIN: 10.82 MIN: 10.83 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_3d - Data Type: bf16bf16bf16 - Engine: CPU b a 3 6 9 12 15 11.14 11.34 MIN: 10.81 MIN: 10.8 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 200 400 600 800 1000 906.09 908.25 MIN: 895.06 MIN: 897.69 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: bf16bf16bf16 - Engine: CPU b a 400 800 1200 1600 2000 1632.03 1650.24 MIN: 1624.52 MIN: 1623.91 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 200 400 600 800 1000 897.02 919.84 MIN: 891.38 MIN: 891.16 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
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 50 100 150 200 250 207.53 207.71 1. (CXX) g++ options: -O3 -fopenmp
OpenBenchmarking.org Seconds, Fewer Is Better easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 b a 2 4 6 8 10 8.418 8.422 1. (CXX) g++ options: -O3 -fopenmp
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU a b 2 4 6 8 10 6.77 6.74 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 2023.2.dev Model: Face Detection FP16 - Device: CPU a b 400 800 1200 1600 2000 1758.87 1768.54 MIN: 1482.92 / MAX: 1874.48 MIN: 1535.35 / MAX: 1891.91 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 2023.2.dev Model: Person Detection FP16 - Device: CPU a b 6 12 18 24 30 26.48 26.21 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 2023.2.dev Model: Person Detection FP16 - Device: CPU a b 100 200 300 400 500 453.11 457.70 MIN: 403.13 / MAX: 481.9 MIN: 398.71 / MAX: 491.98 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 2023.2.dev Model: Person Detection FP32 - Device: CPU a b 6 12 18 24 30 26.51 26.25 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 2023.2.dev Model: Person Detection FP32 - Device: CPU a b 100 200 300 400 500 452.46 457.00 MIN: 411.37 / MAX: 487.12 MIN: 399.1 / MAX: 493.17 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 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU b a 30 60 90 120 150 142.30 140.54 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 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU b a 20 40 60 80 100 84.25 85.30 MIN: 27.82 / MAX: 110.22 MIN: 26.46 / MAX: 114.74 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 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU b a 6 12 18 24 30 26.97 26.96 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 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU a b 100 200 300 400 500 444.06 444.29 MIN: 383.91 / MAX: 504.74 MIN: 397.9 / MAX: 483.36 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 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU b a 160 320 480 640 800 765.16 759.10 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 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU b a 4 8 12 16 20 15.65 15.78 MIN: 7.87 / MAX: 28.02 MIN: 5.06 / MAX: 28.03 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 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU a b 13 26 39 52 65 58.37 58.28 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 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU a b 50 100 150 200 250 205.41 205.72 MIN: 82.28 / MAX: 237.08 MIN: 128.59 / MAX: 235.62 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 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU b a 160 320 480 640 800 758.98 756.48 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 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU b a 4 8 12 16 20 15.77 15.82 MIN: 11.02 / MAX: 36.31 MIN: 5.65 / MAX: 27.4 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 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU a b 170 340 510 680 850 766.69 763.83 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 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU a b 6 12 18 24 30 23.43 23.52 MIN: 12.5 / MAX: 52.05 MIN: 17.2 / MAX: 43.84 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 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU b a 700 1400 2100 2800 3500 3192.8 3190.1 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 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU a b 1.2578 2.5156 3.7734 5.0312 6.289 5.59 5.59 MIN: 3.45 / MAX: 19.52 MIN: 3.32 / MAX: 11.01 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 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU a b 50 100 150 200 250 232.23 229.51 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 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU a b 12 24 36 48 60 51.60 52.23 MIN: 19.06 / MAX: 67.49 MIN: 40.9 / MAX: 61.6 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 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU a b 20 40 60 80 100 78.93 78.36 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 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU a b 30 60 90 120 150 151.95 152.93 MIN: 135.3 / MAX: 190.42 MIN: 112.74 / MAX: 177.47 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 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU b a 600 1200 1800 2400 3000 2734.29 2725.10 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 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU b a 2 4 6 8 10 6.57 6.58 MIN: 5.15 / MAX: 22.73 MIN: 3.85 / MAX: 17.42 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 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU b a 70 140 210 280 350 322.81 322.01 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 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU b a 9 18 27 36 45 37.14 37.23 MIN: 14.14 / MAX: 51.96 MIN: 11.02 / MAX: 50.81 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 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU b a 40 80 120 160 200 174.60 171.99 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 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU b a 20 40 60 80 100 103.02 104.57 MIN: 78.68 / MAX: 167.4 MIN: 61.98 / MAX: 160.39 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 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU a b 4K 8K 12K 16K 20K 18225.98 18196.60 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 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU a b 0.2183 0.4366 0.6549 0.8732 1.0915 0.97 0.97 MIN: 0.56 / MAX: 8.09 MIN: 0.56 / MAX: 15.72 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 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU a b 50 100 150 200 250 208.24 150.46 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 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU a b 30 60 90 120 150 86.37 119.54 MIN: 64.91 / MAX: 129.38 MIN: 66.67 / MAX: 150.45 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 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU b a 8K 16K 24K 32K 40K 35584.44 35356.18 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 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU a b 0.108 0.216 0.324 0.432 0.54 0.48 0.48 MIN: 0.29 / MAX: 14.81 MIN: 0.28 / MAX: 12.73 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
QMCPACK QMCPACK is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code making use of MPI for this benchmark of the H20 example code. QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids. QMCPACK is supported by the U.S. Department of Energy. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Total Execution Time - Seconds, Fewer Is Better QMCPACK 3.17.1 Input: H4_ae b a 5 10 15 20 25 19.31 20.61 1. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl
OpenBenchmarking.org Total Execution Time - Seconds, Fewer Is Better QMCPACK 3.17.1 Input: Li2_STO_ae a b 50 100 150 200 250 219.65 222.42 1. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl
OpenBenchmarking.org Total Execution Time - Seconds, Fewer Is Better QMCPACK 3.17.1 Input: LiH_ae_MSD b a 20 40 60 80 100 106.32 106.57 1. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl
OpenBenchmarking.org Total Execution Time - Seconds, Fewer Is Better QMCPACK 3.17.1 Input: simple-H2O b a 10 20 30 40 50 42.48 42.51 1. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl
OpenBenchmarking.org Total Execution Time - Seconds, Fewer Is Better QMCPACK 3.17.1 Input: O_ae_pyscf_UHF a b 50 100 150 200 250 238.00 241.13 1. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl
OpenBenchmarking.org Total Execution Time - Seconds, Fewer Is Better QMCPACK 3.17.1 Input: FeCO6_b3lyp_gms b a 40 80 120 160 200 183.17 183.42 1. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl
Cpuminer-Opt Cpuminer-Opt is a fork of cpuminer-multi that carries a wide range of CPU performance optimizations for measuring the potential cryptocurrency mining performance of the CPU/processor with a wide variety of cryptocurrencies. The benchmark reports the hash speed for the CPU mining performance for the selected cryptocurrency. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 23.5 Algorithm: Magi a b 90 180 270 360 450 422.16 422.06 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 23.5 Algorithm: Myriad-Groestl b a 1600 3200 4800 6400 8000 7651.61 7629.51 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 23.5 Algorithm: Triple SHA-256, Onecoin b a 11K 22K 33K 44K 55K 53490 53370 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
Embree OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer - Model: Crown a b 5 10 15 20 25 20.27 20.16 MIN: 20.03 / MAX: 20.57 MIN: 19.94 / MAX: 20.5
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Crown a b 4 8 12 16 20 17.72 17.65 MIN: 17.45 / MAX: 18.04 MIN: 17.4 / MAX: 17.92
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer - Model: Asian Dragon b a 6 12 18 24 30 23.14 23.00 MIN: 22.98 / MAX: 23.37 MIN: 22.82 / MAX: 23.22
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj a b 5 10 15 20 25 20.72 20.69 MIN: 20.56 / MAX: 20.92 MIN: 20.55 / MAX: 20.9
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon a b 5 10 15 20 25 22.85 22.84 MIN: 22.67 / MAX: 23.07 MIN: 22.66 / MAX: 23.08
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj b a 5 10 15 20 25 19.63 19.61 MIN: 19.48 / MAX: 19.83 MIN: 19.46 / MAX: 19.85
OSPRay Studio Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU b a 1400 2800 4200 5600 7000 6463 6468
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 16MB a b 1600 3200 4800 6400 8000 7457.4 7424.4 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 32MB b a 1600 3200 4800 6400 8000 7424.0 7361.7 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 64MB b a 1400 2800 4200 5600 7000 6563.5 6560.7 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 8MB a b 2K 4K 6K 8K 10K 10371.6 10336.6 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 128MB a b 1200 2400 3600 4800 6000 5468.8 5457.9 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 256MB b a 900 1800 2700 3600 4500 4429.6 4399.7 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 8MB a b 2K 4K 6K 8K 10K 8267.5 8258.4 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 16MB a b 2K 4K 6K 8K 10K 9855.4 9737.2 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 32MB b a 2K 4K 6K 8K 10K 7847.7 7828.9 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 64MB b a 1500 3000 4500 6000 7500 6779.6 6761.1 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 16MB b a 2K 4K 6K 8K 10K 8211.3 8107.4 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 32MB b a 1600 3200 4800 6400 8000 7651.2 7590.0 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 64MB b a 1500 3000 4500 6000 7500 6790.6 6752.2 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 128MB b a 1200 2400 3600 4800 6000 5490.8 5467.9 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 256MB b a 900 1800 2700 3600 4500 4248.9 4239.4 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 128MB b a 1200 2400 3600 4800 6000 5636.2 5578.8 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 256MB b a 1000 2000 3000 4000 5000 4516.0 4497.3 1. (CC) gcc options: -std=gnu99 -O3 -ldl -lrt -lm
DuckDB DuckDB is an in-progress SQL OLAP database management system optimized for analytics and features a vectorized and parallel engine. Learn more via the OpenBenchmarking.org test page.
Benchmark: IMDB
a: The test run did not produce a result.
b: The test run did not produce a result.
Benchmark: TPC-H Parquet
a: The test run did not produce a result.
b: 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-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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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 -vProcessor Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0x5003604Python Notes: Python 3.10.12Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Mitigation of Enhanced IBRS + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Mitigation of TSX disabled
Testing initiated at 5 November 2023 17:47 by user pts.
b Processor: Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads), Motherboard: ASRock X299 Steel Legend (P1.30 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 32GB, Disk: Samsung SSD 970 PRO 512GB, Graphics: llvmpipe, Audio: Realtek ALC1220, Network: Intel I219-V + Intel I211
OS: Ubuntu 22.04, Kernel: 6.2.0-33-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server 1.21.1.3, OpenGL: 4.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits), Vulkan: 1.2.204, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 1024x768
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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 -vProcessor Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0x5003604Python Notes: Python 3.10.12Security Notes: gather_data_sampling: Mitigation of Microcode + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Mitigation of Enhanced IBRS + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Mitigation of TSX disabled
Testing initiated at 5 November 2023 20:32 by user pts.