pangolin scikit

Tests for a future article. AMD Ryzen 7 6800U testing with a System76 Pangolin (ARB928_V00.01_T0022ASY6_ms BIOS) and AMD Rembrandt 512MB on Pop 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2305107-NE-PANGOLINS94
Jump To Table - Results

Statistics

Remove Outliers Before Calculating Averages

Graph Settings

Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
a
May 10 2023
  3 Hours, 37 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


pangolin scikitOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 7 6800U @ 2.70GHz (8 Cores / 16 Threads)System76 Pangolin (ARB928_V00.01_T0022ASY6_ms BIOS)AMD Device 14b532GB1000GB Samsung SSD 980 PRO 1TBAMD Rembrandt 512MB (2200/400MHz)AMD Device 1640Realtek RTL8111/8168/8411 + MEDIATEK Device 0608Pop 22.046.2.6-76060206-generic (x86_64)GNOME Shell 42.5X Server 1.21.1.34.6 Mesa 22.3.5 (LLVM 15.0.6 DRM 3.49)1.3.230GCC 11.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionPangolin Scikit BenchmarksSystem 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-xKiWfi/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-xKiWfi/gcc-11-11.3.0/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: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa404102 - Python 3.10.6- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

pangolin scikitscikit-learn: Hist Gradient Boosting Adultscikit-learn: Covertype Dataset Benchmarkscikit-learn: Sample Without Replacementscikit-learn: Hist Gradient Boostingscikit-learn: Plot Incremental PCAscikit-learn: Isotonic / Logisticscikit-learn: TSNE MNIST Datasetscikit-learn: LocalOutlierFactorscikit-learn: Feature Expansionsscikit-learn: Plot OMP vs. LARSscikit-learn: Plot Hierarchicalscikit-learn: Text Vectorizersscikit-learn: Plot Fast KMeansscikit-learn: Isolation Forestscikit-learn: Plot Lasso Pathscikit-learn: SGDOneClassSVMscikit-learn: SGD Regressionscikit-learn: Plot Neighborsscikit-learn: MNIST Datasetscikit-learn: Plot Wardscikit-learn: Sparsifyscikit-learn: Lassoscikit-learn: Treescikit-learn: SAGAscikit-learn: GLMscikit-learn: Glmneta72.391396.236119.54398.24940.6381412.579280.73265.218141.59687.322198.260.792231.527258.728224.938279.84102.353132.07159.81258.56884.497427.94142.388770.164357.839OpenBenchmarking.org

Scikit-Learn

Scikit-learn is a Python module for machine learning built on NumPy, SciPy, and is BSD-licensed. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Adulta163248648072.391. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Covertype Dataset Benchmarka90180270360450396.241. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sample Without Replacementa306090120150119.541. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boostinga2040608010098.251. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Incremental PCAa91827364540.641. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isotonic / Logistica300600900120015001412.581. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: TSNE MNIST Dataseta60120180240300280.731. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: LocalOutlierFactora153045607565.221. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Feature Expansionsa306090120150141.601. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot OMP vs. LARSa2040608010087.321. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Hierarchicala4080120160200198.21. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Text Vectorizersa142842567060.791. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Fast KMeansa50100150200250231.531. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isolation Foresta60120180240300258.731. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Lasso Patha50100150200250224.941. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGDOneClassSVMa60120180240300279.841. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGD Regressiona20406080100102.351. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Neighborsa306090120150132.071. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: MNIST Dataseta132639526559.811. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Warda132639526558.571. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparsifya2040608010084.501. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Lassoa90180270360450427.941. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Treea102030405042.391. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SAGAa170340510680850770.161. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: GLMa80160240320400357.841. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

Benchmark: RCV1 Logreg Convergencet

a: The test quit with a non-zero exit status. E: IndexError: list index out of range

Benchmark: Isotonic / Pathological

a: The test quit with a non-zero exit status.

Benchmark: Plot Parallel Pairwise

a: The test quit with a non-zero exit status. E: numpy.core._exceptions._ArrayMemoryError: Unable to allocate 74.5 GiB for an array with shape (100000, 100000) and data type float64

Benchmark: Glmnet

a: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'glmnet'