mltest
2 x Intel Xeon Gold 6126 testing with a Inspur YZMB-01130-101 and ASPEED ASPEED Family on Ubuntu 16.04 via the Phoronix Test Suite.
mltest
Processor: 2 x Intel Xeon Gold 6126 @ 3.70GHz (24 Cores), Motherboard: Inspur YZMB-01130-101, Chipset: Intel Device 2020, Memory: 258048MB, Disk: 537GB MR9361-8i + 644GB MR9361-8i + 6018GB MR9361-8i, Graphics: ASPEED ASPEED Family, Audio: NVIDIA Device 10f7, Network: Intel 82571EB Gigabit
OS: Ubuntu 16.04, Kernel: 4.4.0-116-generic (x86_64), Display Driver: modesetting 1.18.4, Compiler: GCC 5.4.0 20160609 + CUDA 10.1, File-System: ext4, Screen Resolution: 1920x1080
Compiler Notes: --build=x86_64-linux-gnu --disable-browser-plugin --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-arch-directory=amd64 --with-default-libstdcxx-abi=new --with-multilib-list=m32,m64,mx32 --with-tune=generic -v
Processor Notes: Scaling Governor: intel_pstate powersave
System Notes: Python 3.7.3.
Numpy Benchmark
This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.
DeepSpeech
Mozilla DeepSpeech is a speech-to-text engine powered by TensorFlow for machine learning and derived from Baidu's Deep Speech research paper. This test profile times the speech-to-text process for a roughly three minute audio recording. Learn more via the OpenBenchmarking.org test page.
Numenta Anomaly Benchmark
Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
Scikit-Learn
Scikit-learn is a Python module for machine learning Learn more via the OpenBenchmarking.org test page.
mltest
Processor: 2 x Intel Xeon Gold 6126 @ 3.70GHz (24 Cores), Motherboard: Inspur YZMB-01130-101, Chipset: Intel Device 2020, Memory: 258048MB, Disk: 537GB MR9361-8i + 644GB MR9361-8i + 6018GB MR9361-8i, Graphics: ASPEED ASPEED Family, Audio: NVIDIA Device 10f7, Network: Intel 82571EB Gigabit
OS: Ubuntu 16.04, Kernel: 4.4.0-116-generic (x86_64), Display Driver: modesetting 1.18.4, Compiler: GCC 5.4.0 20160609 + CUDA 10.1, File-System: ext4, Screen Resolution: 1920x1080
Compiler Notes: --build=x86_64-linux-gnu --disable-browser-plugin --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-gnu-unique-object --enable-gtk-cairo --enable-java-awt=gtk --enable-java-home --enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-arch-directory=amd64 --with-default-libstdcxx-abi=new --with-multilib-list=m32,m64,mx32 --with-tune=generic -v
Processor Notes: Scaling Governor: intel_pstate powersave
System Notes: Python 3.7.3.
Testing initiated at 6 July 2020 00:40 by user user1.