2 x Intel Xeon Gold 6138 testing with a TYAN S7106 (V2.00.B20 BIOS) and llvmpipe 93GB on Ubuntu 18.04 via the Phoronix Test Suite.
Samsung SSD 860 - 2 x Intel Xeon Gold 6138 Processor: 2 x Intel Xeon Gold 6138 @ 3.70GHz (40 Cores / 80 Threads), Motherboard: TYAN S7106 (V2.00.B20 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 96256MB, Disk: 500GB Samsung SSD 860, Graphics: llvmpipe 93GB, Monitor: VE228, Network: 2 x Intel I210 + 2 x QLogic cLOM8214 1/10GbE
OS: Ubuntu 18.04, Kernel: 5.0.0-31-generic (x86_64), Desktop: GNOME Shell 3.28.4, Display Server: X Server 1.20.4, Display Driver: modesetting 1.20.4, OpenGL: 3.3 Mesa 19.0.8 (LLVM 8.0 256 bits), Compiler: GCC 7.4.0, File-System: ext4, Screen Resolution: 1920x1080
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --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 --with-tune=generic --without-cuda-driver -vDisk Notes: MQ-DEADLINE / errors=remount-ro,relatime,rwProcessor Notes: Scaling Governor: intel_pstate powersaveSecurity Notes: l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Vulnerable; SMT vulnerable + meltdown: Vulnerable + spec_store_bypass: Vulnerable + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Vulnerable IBPB: disabled STIBP: disabled
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_3d - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 2 4 6 8 10 SE +/- 0.01, N = 3 7.15 MIN: 7.04 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_1d - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.3938 0.7876 1.1814 1.5752 1.969 SE +/- 0.00, N = 3 1.75 MIN: 1.66 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_all - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 500 1000 1500 2000 2500 SE +/- 4.88, N = 3 2527.50 MIN: 2501.4 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_all - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 200 400 600 800 1000 SE +/- 2.15, N = 3 1135.86 MIN: 1115.56 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: IP Batch 1D - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.5805 1.161 1.7415 2.322 2.9025 SE +/- 0.02, N = 3 2.58 MIN: 2.25 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_alexnet - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 20 40 60 80 100 SE +/- 0.08, N = 3 87.00 MIN: 84.24 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 14 28 42 56 70 SE +/- 0.06, N = 3 60.37 MIN: 57.42 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 9 18 27 36 45 SE +/- 0.07, N = 3 40.19 MIN: 37.75 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_3d - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 2 4 6 8 10 SE +/- 0.04, N = 3 6.27 MIN: 5.98 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Recurrent Neural Network Training - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 60 120 180 240 300 SE +/- 3.58, N = 3 256.20 MIN: 237.44 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: IP Batch 1D - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 1.1093 2.2186 3.3279 4.4372 5.5465 SE +/- 0.06, N = 3 4.93 MIN: 4.41 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: IP Batch All - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 30 60 90 120 150 SE +/- 1.39, N = 3 150.67 MIN: 88.28 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: IP Batch All - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 1.0305 2.061 3.0915 4.122 5.1525 SE +/- 0.02, N = 3 4.58 MIN: 4.21 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: IP Batch 1D - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.4793 0.9586 1.4379 1.9172 2.3965 SE +/- 0.00, N = 3 2.13 MIN: 1.95 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: IP Batch All - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 3 6 9 12 15 SE +/- 0.01, N = 3 11.53 MIN: 11.09 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 5 10 15 20 25 SE +/- 16.62, N = 12 19.54 MIN: 0.84 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_all - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 200 400 600 800 1000 SE +/- 0.86, N = 3 854.68 MIN: 834.93 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 800 1600 2400 3200 4000 SE +/- 1.55, N = 3 3937.85 MIN: 3933.05 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_3d - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 1000 2000 3000 4000 5000 SE +/- 6.67, N = 3 4593.53 MIN: 4569.73 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_3d - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 3 6 9 12 15 SE +/- 0.01, N = 3 13.02 MIN: 12.62 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_all - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 700 1400 2100 2800 3500 SE +/- 0.86, N = 3 3122.94 MIN: 3098.68 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_3d - Data Type: f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.441 0.882 1.323 1.764 2.205 SE +/- 0.00, N = 3 1.96 MIN: 1.89 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_1d - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 2 4 6 8 10 SE +/- 0.06, N = 14 6.55 MIN: 6.27 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Hair Samsung SSD 860 - 2 x Intel Xeon Gold 6138 3 6 9 12 15 SE +/- 0.02, N = 3 11.27 1. (CXX) g++ options: -std=c++0x -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -mfma -mbmi2 -mavx512f -mavx512vl -mavx512cd -mavx512dq -mavx512bw -mno-sse4a -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512pf -mno-avx512er -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -ljpeg -lpthread -ldl
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_googlenet_v3 - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 30 60 90 120 150 SE +/- 0.21, N = 3 152.60 MIN: 150.1 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Water Caustic Samsung SSD 860 - 2 x Intel Xeon Gold 6138 6 12 18 24 30 SE +/- 0.10, N = 3 24.96 1. (CXX) g++ options: -std=c++0x -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -mfma -mbmi2 -mavx512f -mavx512vl -mavx512cd -mavx512dq -mavx512bw -mno-sse4a -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512pf -mno-avx512er -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -ljpeg -lpthread -ldl
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Deconvolution Batch deconv_all - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 600 1200 1800 2400 3000 SE +/- 1.81, N = 3 2759.56 MIN: 2723.66 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Non-Exponential Samsung SSD 860 - 2 x Intel Xeon Gold 6138 1.3478 2.6956 4.0434 5.3912 6.739 SE +/- 0.18, N = 15 5.99 1. (CXX) g++ options: -std=c++0x -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -mfma -mbmi2 -mavx512f -mavx512vl -mavx512cd -mavx512dq -mavx512bw -mno-sse4a -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512pf -mno-avx512er -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -ljpeg -lpthread -ldl
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Volumetric Caustic Samsung SSD 860 - 2 x Intel Xeon Gold 6138 4 8 12 16 20 SE +/- 0.20, N = 5 16.40 1. (CXX) g++ options: -std=c++0x -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -mfma -mbmi2 -mavx512f -mavx512vl -mavx512cd -mavx512dq -mavx512bw -mno-sse4a -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512pf -mno-avx512er -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -ljpeg -lpthread -ldl
OpenBenchmarking.org Frames Per Second, More Is Better Embree 3.6.1 Binary: Pathtracer ISPC - Model: Crown Samsung SSD 860 - 2 x Intel Xeon Gold 6138 7 14 21 28 35 SE +/- 0.01, N = 3 31.97 MIN: 31.38 / MAX: 32.6
OpenBenchmarking.org Frames Per Second, More Is Better Embree 3.6.1 Binary: Pathtracer - Model: Asian Dragon Samsung SSD 860 - 2 x Intel Xeon Gold 6138 8 16 24 32 40 SE +/- 0.13, N = 3 33.66 MIN: 32.77 / MAX: 35.15
OpenBenchmarking.org Frames Per Second, More Is Better Embree 3.6.1 Binary: Pathtracer - Model: Asian Dragon Obj Samsung SSD 860 - 2 x Intel Xeon Gold 6138 7 14 21 28 35 SE +/- 0.11, N = 3 30.59 MIN: 30 / MAX: 31.93
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 6 12 18 24 30 SE +/- 0.04, N = 3 25.27 MIN: 24.47 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
OpenBenchmarking.org Frames Per Second, More Is Better Embree 3.6.1 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Samsung SSD 860 - 2 x Intel Xeon Gold 6138 8 16 24 32 40 SE +/- 0.02, N = 3 35.85 MIN: 35.39 / MAX: 36.48
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.2 Scene: Rainbow Colors and Prism Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.2475 0.495 0.7425 0.99 1.2375 SE +/- 0.09, N = 12 1.10 MIN: 0.51 / MAX: 1.54
OSPray Intel OSPray is a portable ray-tracing engine for high-performance, high-fidenlity scientific 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 FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis Samsung SSD 860 - 2 x Intel Xeon Gold 6138 10 20 30 40 50 SE +/- 0.00, N = 12 41.67 MIN: 25 / MAX: 43.48
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: SciVis Samsung SSD 860 - 2 x Intel Xeon Gold 6138 2 4 6 8 10 SE +/- 0.00, N = 10 7.04 MIN: 5.62 / MAX: 7.09
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: Path Tracer Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.8618 1.7236 2.5854 3.4472 4.309 SE +/- 0.00, N = 12 3.83 MIN: 2.74 / MAX: 3.86
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: SciVis Samsung SSD 860 - 2 x Intel Xeon Gold 6138 12 24 36 48 60 SE +/- 0.00, N = 15 55.56 MIN: 21.74
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: Path Tracer Samsung SSD 860 - 2 x Intel Xeon Gold 6138 0.8753 1.7506 2.6259 3.5012 4.3765 SE +/- 0.01, N = 3 3.89 MIN: 3.53 / MAX: 3.92
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: SciVis Samsung SSD 860 - 2 x Intel Xeon Gold 6138 10 20 30 40 50 SE +/- 0.00, N = 13 45.45 MIN: 16.39 / MAX: 47.62
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer Samsung SSD 860 - 2 x Intel Xeon Gold 6138 3 6 9 12 15 SE +/- 0.04, N = 3 10.49 MIN: 8.62 / MAX: 10.75
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: Path Tracer Samsung SSD 860 - 2 x Intel Xeon Gold 6138 110 220 330 440 550 500 MIN: 250
OpenSSL OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test measures the RSA 4096-bit performance of OpenSSL. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Signs Per Second, More Is Better OpenSSL 1.1.1 RSA 4096-bit Performance Samsung SSD 860 - 2 x Intel Xeon Gold 6138 2K 4K 6K 8K 10K SE +/- 28.11, N = 3 7829.70 1. (CC) gcc options: -pthread -m64 -O3 -lssl -lcrypto -ldl
MKL-DNN DNNL This is a test of the Intel MKL-DNN (DNNL / Deep Neural Network Library) 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN DNNL 1.1 Harness: Convolution Batch conv_alexnet - Data Type: bf16bf16bf16 Samsung SSD 860 - 2 x Intel Xeon Gold 6138 120 240 360 480 600 SE +/- 0.78, N = 3 567.94 MIN: 563.58 1. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl
Samsung SSD 860 - 2 x Intel Xeon Gold 6138 Processor: 2 x Intel Xeon Gold 6138 @ 3.70GHz (40 Cores / 80 Threads), Motherboard: TYAN S7106 (V2.00.B20 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 96256MB, Disk: 500GB Samsung SSD 860, Graphics: llvmpipe 93GB, Monitor: VE228, Network: 2 x Intel I210 + 2 x QLogic cLOM8214 1/10GbE
OS: Ubuntu 18.04, Kernel: 5.0.0-31-generic (x86_64), Desktop: GNOME Shell 3.28.4, Display Server: X Server 1.20.4, Display Driver: modesetting 1.20.4, OpenGL: 3.3 Mesa 19.0.8 (LLVM 8.0 256 bits), Compiler: GCC 7.4.0, File-System: ext4, Screen Resolution: 1920x1080
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --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 --with-tune=generic --without-cuda-driver -vDisk Notes: MQ-DEADLINE / errors=remount-ro,relatime,rwProcessor Notes: Scaling Governor: intel_pstate powersaveSecurity Notes: l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Vulnerable; SMT vulnerable + meltdown: Vulnerable + spec_store_bypass: Vulnerable + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Vulnerable IBPB: disabled STIBP: disabled
Testing initiated at 13 October 2019 09:49 by user phoronix.