python-z-1
AMD Ryzen 5 3400G testing with a LENOVO 3706 (O4DKT35A BIOS) and AMD Picasso 2GB on Ubuntu 20.04 via the Phoronix Test Suite.
AMD Ryzen 5 3400G
Processor: AMD Ryzen 5 3400G @ 3.70GHz (4 Cores / 8 Threads), Motherboard: LENOVO 3706 (O4DKT35A BIOS), Chipset: AMD Raven/Raven2, Memory: 14GB, Disk: 500GB Western Digital WD5000LPVX-8, Graphics: AMD Picasso 2GB (1400/1333MHz), Audio: AMD Raven/Raven2/Fenghuang, Monitor: DP2VGA V226, Network: Realtek RTL8111/8168/8411 + Realtek RTL8821CE 802.11ac PCIe
OS: Ubuntu 20.04, Kernel: 5.4.0-80-generic (x86_64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.9, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1024x768
Kernel Notes: Transparent Huge Pages: madvise
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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --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
Processor Notes: Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0x8108102
Python Notes: Python 3.8.10
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected
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.
Numpy Benchmark
This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.
Mlpack Benchmark
Mlpack benchmark scripts for machine learning libraries 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.
PyPerformance
PyPerformance is the reference Python performance benchmark suite. 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.
PyPerformance
PyPerformance is the reference Python performance benchmark suite. 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.
PyPerformance
PyPerformance is the reference Python performance benchmark suite. Learn more via the OpenBenchmarking.org test page.
Mlpack Benchmark
Mlpack benchmark scripts for machine learning libraries 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.
Cython Benchmark
Cython provides a superset of Python that is geared to deliver C-like levels of performance. This test profile makes use of Cython's bundled benchmark tests and runs an N-Queens sample test as a simple benchmark to the system's Cython performance. Learn more via the OpenBenchmarking.org test page.
PyBench
This test profile reports the total time of the different average timed test results from PyBench. PyBench reports average test times for different functions such as BuiltinFunctionCalls and NestedForLoops, with this total result providing a rough estimate as to Python's average performance on a given system. This test profile runs PyBench each time for 20 rounds. Learn more via the OpenBenchmarking.org test page.
PyPerformance
PyPerformance is the reference Python performance benchmark suite. Learn more via the OpenBenchmarking.org test page.
AMD Ryzen 5 3400G
Processor: AMD Ryzen 5 3400G @ 3.70GHz (4 Cores / 8 Threads), Motherboard: LENOVO 3706 (O4DKT35A BIOS), Chipset: AMD Raven/Raven2, Memory: 14GB, Disk: 500GB Western Digital WD5000LPVX-8, Graphics: AMD Picasso 2GB (1400/1333MHz), Audio: AMD Raven/Raven2/Fenghuang, Monitor: DP2VGA V226, Network: Realtek RTL8111/8168/8411 + Realtek RTL8821CE 802.11ac PCIe
OS: Ubuntu 20.04, Kernel: 5.4.0-80-generic (x86_64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.9, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1024x768
Kernel Notes: Transparent Huge Pages: madvise
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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --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
Processor Notes: Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0x8108102
Python Notes: Python 3.8.10
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 28 July 2021 16:27 by user test.