Intel Core i7-6770HQ testing with a Intel NUC6i7KYB (KYSKLi70.86A.0037.2016.0603.1032 BIOS) and Intel Iris Pro 580 3GB on Ubuntu 19.04 via the Phoronix Test Suite.
Core i7 6770HQ Processor: Intel Core i7-6770HQ @ 3.50GHz (4 Cores / 8 Threads), Motherboard: Intel NUC6i7KYB (KYSKLi70.86A.0037.2016.0603.1032 BIOS), Chipset: Intel Xeon E3-1200 v5/E3-1500, Memory: 32768MB, Disk: Samsung SSD 950 PRO 512GB, Graphics: Intel Iris Pro 580 3GB (950MHz), Audio: Realtek ALC233, Monitor: DELL P2415Q, Network: Intel I219-LM + Intel 8260
OS: Ubuntu 19.04, Kernel: 5.0.0-13-generic (x86_64), Desktop: GNOME Shell 3.32.0, Display Server: X Server 1.20.4, Display Driver: modesetting 1.20.4, OpenGL: 4.5 Mesa 19.1.0-devel (git-bdd273d 2019-05-06 disco-oibaf-ppa), OpenCL: OpenCL 1.2 pocl +Asserts LLVM 6.0.1 SLEEF DISTRO POCL_DEBUG, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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 -vProcessor Notes: Scaling Governor: intel_pstate powersaveSecurity Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + SSB disabled via prctl and seccomp + PTE Inversion; VMX: conditional cache flushes SMT vulnerable
Core i7 6770HQ OpenBenchmarking.org Phoronix Test Suite Intel Core i7-6770HQ @ 3.50GHz (4 Cores / 8 Threads) Intel NUC6i7KYB (KYSKLi70.86A.0037.2016.0603.1032 BIOS) Intel Xeon E3-1200 v5/E3-1500 32768MB Samsung SSD 950 PRO 512GB Intel Iris Pro 580 3GB (950MHz) Realtek ALC233 DELL P2415Q Intel I219-LM + Intel 8260 Ubuntu 19.04 5.0.0-13-generic (x86_64) GNOME Shell 3.32.0 X Server 1.20.4 modesetting 1.20.4 4.5 Mesa 19.1.0-devel (git-bdd273d 2019-05-06 disco-oibaf-ppa) OpenCL 1.2 pocl +Asserts LLVM 6.0.1 SLEEF DISTRO POCL_DEBUG GCC 8.3.0 ext4 3840x2160 Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Compiler File-System Screen Resolution Core I7 6770HQ Benchmarks System Logs - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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 -v - Scaling Governor: intel_pstate powersave - KPTI + __user pointer sanitization + Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + SSB disabled via prctl and seccomp + PTE Inversion; VMX: conditional cache flushes SMT vulnerable
Core i7 6770HQ compress-xz: Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9 mkl-dnn: Convolution Batch conv_3d - u8s8u8s32 mbw: Memory Copy - 128 MiB mbw: Memory Copy - 512 MiB mbw: Memory Copy - 1024 MiB mkl-dnn: Convolution Batch conv_all - u8s8u8s32 mbw: Memory Copy - 4096 MiB mkl-dnn: Deconvolution Batch deconv_3d - f32 mkl-dnn: Convolution Batch conv_alexnet - f32 mkl-dnn: Convolution Batch conv_all - f32 mkl-dnn: Deconvolution Batch deconv_1d - f32 mkl-dnn: IP Batch All - u8s8f32s32 mkl-dnn: Convolution Batch conv_3d - f32 mkl-dnn: IP Batch 1D - u8s8f32s32 mkl-dnn: Convolution Batch conv_3d - u8s8f32s32 mkl-dnn: IP Batch All - f32 mkl-dnn: IP Batch 1D - u8s8u8s32 mkl-dnn: IP Batch 1D - f32 mbw: Memory Copy - 8192 MiB mbw: Memory Copy, Fixed Block Size - 128 MiB mkl-dnn: Deconvolution Batch deconv_all - f32 mkl-dnn: IP Batch All - u8s8u8s32 mbw: Memory Copy, Fixed Block Size - 512 MiB mkl-dnn: Convolution Batch conv_googlenet_v3 - f32 mbw: Memory Copy, Fixed Block Size - 1024 MiB mkl-dnn: Convolution Batch conv_all - u8s8f32s32 mkl-dnn: Convolution Batch conv_alexnet - u8s8f32s32 mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8u8s32 mkl-dnn: Deconvolution Batch deconv_3d - u8s8f32s32 mkl-dnn: Deconvolution Batch deconv_all - u8s8u8s32 mkl-dnn: Convolution Batch conv_alexnet - u8s8u8s32 mkl-dnn: Deconvolution Batch deconv_1d - u8s8f32s32 mkl-dnn: Deconvolution Batch deconv_3d - u8s8u8s32 mkl-dnn: Deconvolution Batch deconv_1d - u8s8u8s32 mbw: Memory Copy, Fixed Block Size - 4096 MiB mbw: Memory Copy, Fixed Block Size - 8192 MiB mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8f32s32 hpcg: compress-zstd: Compressing ubuntu-16.04.3-server-i386.img, Compression Level 19 aom-av1: AV1 Video Encoding vpxenc: vpxenc VP9 1080p Video Encode svt-vp9: 1080p 8-bit YUV To VP9 Video Encode x264: H.264 Video Encoding svt-av1: 1080p 8-bit YUV To AV1 Video Encode x265: H.265 1080p Video Encoding svt-hevc: 1080p 8-bit YUV To HEVC Video Encode ffmpeg: H.264 HD To NTSC DV Core i7 6770HQ 71.48 47125.60 10261.74 9962.77 9917.91 50269.17 9904.86 16.99 967.59 7364.37 15.01 135.90 42.22 8.28 45975.10 197.77 8.32 14.03 9855.08 6836.37 5728.47 132.26 6683.64 409.61 6679.19 49499.70 1426.82 764.45 26262.47 51594.73 1488.45 15341.73 28863.83 17178.90 6681.29 6598.30 723.41 1.04 44.10 0.15 21.38 21.21 36.26 6.95 20.23 76.93 7.08 OpenBenchmarking.org
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Convolution Batch conv_3d - Data Type: u8s8u8s32 Core i7 6770HQ 10K 20K 30K 40K 50K SE +/- 99.60, N = 3 47125.60 MIN: 46547.3 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy - Array Size: 512 MiB Core i7 6770HQ 2K 4K 6K 8K 10K SE +/- 58.98, N = 3 9962.77 1. (CC) gcc options: -O3 -march=native
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy - Array Size: 1024 MiB Core i7 6770HQ 2K 4K 6K 8K 10K SE +/- 62.73, N = 3 9917.91 1. (CC) gcc options: -O3 -march=native
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Convolution Batch conv_all - Data Type: u8s8u8s32 Core i7 6770HQ 11K 22K 33K 44K 55K SE +/- 33.25, N = 3 50269.17 MIN: 49244 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Deconvolution Batch deconv_3d - Data Type: f32 Core i7 6770HQ 4 8 12 16 20 SE +/- 0.04, N = 3 16.99 MIN: 16.16 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_alexnet - Data Type: f32 Core i7 6770HQ 200 400 600 800 1000 SE +/- 4.12, N = 3 967.59 MIN: 945.51 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_all - Data Type: f32 Core i7 6770HQ 1600 3200 4800 6400 8000 SE +/- 10.00, N = 3 7364.37 MIN: 7269.07 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Deconvolution Batch deconv_1d - Data Type: f32 Core i7 6770HQ 4 8 12 16 20 SE +/- 0.08, N = 3 15.01 MIN: 14.26 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: IP Batch All - Data Type: u8s8f32s32 Core i7 6770HQ 30 60 90 120 150 SE +/- 1.34, N = 3 135.90 MIN: 78.67 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_3d - Data Type: f32 Core i7 6770HQ 10 20 30 40 50 SE +/- 0.63, N = 3 42.22 MIN: 39.39 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: IP Batch 1D - Data Type: u8s8f32s32 Core i7 6770HQ 2 4 6 8 10 SE +/- 0.07, N = 3 8.28 MIN: 6.39 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_3d - Data Type: u8s8f32s32 Core i7 6770HQ 10K 20K 30K 40K 50K SE +/- 103.56, N = 3 45975.10 MIN: 45576.3 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: IP Batch All - Data Type: f32 Core i7 6770HQ 40 80 120 160 200 SE +/- 2.65, N = 3 197.77 MIN: 124.96 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: IP Batch 1D - Data Type: u8s8u8s32 Core i7 6770HQ 2 4 6 8 10 SE +/- 0.09, N = 3 8.32 MIN: 6.5 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: IP Batch 1D - Data Type: f32 Core i7 6770HQ 4 8 12 16 20 SE +/- 0.31, N = 15 14.03 MIN: 10.16 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy, Fixed Block Size - Array Size: 128 MiB Core i7 6770HQ 1500 3000 4500 6000 7500 SE +/- 25.49, N = 3 6836.37 1. (CC) gcc options: -O3 -march=native
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Deconvolution Batch deconv_all - Data Type: f32 Core i7 6770HQ 1200 2400 3600 4800 6000 SE +/- 6.73, N = 3 5728.47 MIN: 5636.01 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: IP Batch All - Data Type: u8s8u8s32 Core i7 6770HQ 30 60 90 120 150 SE +/- 1.33, N = 3 132.26 MIN: 79.55 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32 Core i7 6770HQ 90 180 270 360 450 SE +/- 1.11, N = 3 409.61 MIN: 397.83 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Convolution Batch conv_all - Data Type: u8s8f32s32 Core i7 6770HQ 11K 22K 33K 44K 55K SE +/- 43.10, N = 3 49499.70 MIN: 48554.9 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32s32 Core i7 6770HQ 300 600 900 1200 1500 SE +/- 3.88, N = 3 1426.82 MIN: 1318.74 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8u8s32 Core i7 6770HQ 160 320 480 640 800 SE +/- 3.30, N = 3 764.45 MIN: 703.44 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32s32 Core i7 6770HQ 6K 12K 18K 24K 30K SE +/- 38.44, N = 3 26262.47 MIN: 26134.7 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Deconvolution Batch deconv_all - Data Type: u8s8u8s32 Core i7 6770HQ 11K 22K 33K 44K 55K SE +/- 119.76, N = 3 51594.73 MIN: 50753.4 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Convolution Batch conv_alexnet - Data Type: u8s8u8s32 Core i7 6770HQ 300 600 900 1200 1500 SE +/- 6.13, N = 3 1488.45 MIN: 1380.82 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32s32 Core i7 6770HQ 3K 6K 9K 12K 15K SE +/- 51.98, N = 3 15341.73 MIN: 15192.1 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Deconvolution Batch deconv_3d - Data Type: u8s8u8s32 Core i7 6770HQ 6K 12K 18K 24K 30K SE +/- 1.19, N = 3 28863.83 MIN: 28816.2 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org ms, Fewer Is Better MKL-DNN 2019-04-16 Harness: Deconvolution Batch deconv_1d - Data Type: u8s8u8s32 Core i7 6770HQ 4K 8K 12K 16K 20K SE +/- 2.27, N = 3 17178.90 MIN: 17069.1 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy, Fixed Block Size - Array Size: 8192 MiB Core i7 6770HQ 1400 2800 4200 5600 7000 SE +/- 12.38, N = 3 6598.30 1. (CC) gcc options: -O3 -march=native
MKL-DNN This is a test of the Intel MKL-DNN as the Intel Math Kernel 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 2019-04-16 Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32s32 Core i7 6770HQ 160 320 480 640 800 SE +/- 4.85, N = 3 723.41 MIN: 655.35 1. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl
SVT-VP9 This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-VP9 CPU-based multi-threaded video encoder for the VP9 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 2019-02-17 1080p 8-bit YUV To VP9 Video Encode Core i7 6770HQ 5 10 15 20 25 SE +/- 0.02, N = 3 21.21 1. (CC) gcc options: -fPIE -fPIC -O2 -flto -fvisibility=hidden -mavx -pie -rdynamic -lpthread -lrt -lm
SVT-HEVC This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-HEVC CPU-based multi-threaded video encoder for the HEVC / H.265 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better SVT-HEVC 2019-02-03 1080p 8-bit YUV To HEVC Video Encode Core i7 6770HQ 20 40 60 80 100 SE +/- 0.21, N = 3 76.93 1. (CC) gcc options: -fPIE -fPIC -O2 -flto -fvisibility=hidden -march=native -pie -rdynamic -lpthread -lrt
FFmpeg This test uses FFmpeg for testing the system's audio/video encoding performance. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better FFmpeg 4.0.2 H.264 HD To NTSC DV Core i7 6770HQ 2 4 6 8 10 SE +/- 0.01, N = 3 7.08 1. (CC) gcc options: -lavdevice -lavfilter -lavformat -lavcodec -lswresample -lswscale -lavutil -lXv -lX11 -lXext -lm -lxcb -lxcb-shape -lxcb-xfixes -lasound -lSDL2 -lsndio -pthread -lbz2 -llzma -std=c11 -fomit-frame-pointer -fPIC -O3 -fno-math-errno -fno-signed-zeros -fno-tree-vectorize -MMD -MF -MT
Core i7 6770HQ Processor: Intel Core i7-6770HQ @ 3.50GHz (4 Cores / 8 Threads), Motherboard: Intel NUC6i7KYB (KYSKLi70.86A.0037.2016.0603.1032 BIOS), Chipset: Intel Xeon E3-1200 v5/E3-1500, Memory: 32768MB, Disk: Samsung SSD 950 PRO 512GB, Graphics: Intel Iris Pro 580 3GB (950MHz), Audio: Realtek ALC233, Monitor: DELL P2415Q, Network: Intel I219-LM + Intel 8260
OS: Ubuntu 19.04, Kernel: 5.0.0-13-generic (x86_64), Desktop: GNOME Shell 3.32.0, Display Server: X Server 1.20.4, Display Driver: modesetting 1.20.4, OpenGL: 4.5 Mesa 19.1.0-devel (git-bdd273d 2019-05-06 disco-oibaf-ppa), OpenCL: OpenCL 1.2 pocl +Asserts LLVM 6.0.1 SLEEF DISTRO POCL_DEBUG, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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 -vProcessor Notes: Scaling Governor: intel_pstate powersaveSecurity Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + SSB disabled via prctl and seccomp + PTE Inversion; VMX: conditional cache flushes SMT vulnerable
Testing initiated at 8 May 2019 21:10 by user phoronix.