5900hx scikit learn

AMD Ryzen 9 5900HX testing with a ASUS G513QY v1.0 (G513QY.318 BIOS) and ASUS AMD Cezanne 512MB on Ubuntu 22.10 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 2305113-NE-5900HXSCI86
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May 10 2023
  7 Hours, 56 Minutes
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May 10 2023
  7 Hours, 34 Minutes
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May 11 2023
  7 Hours, 33 Minutes
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  7 Hours, 41 Minutes

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5900hx scikit learnOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 5900HX @ 3.30GHz (8 Cores / 16 Threads)ASUS G513QY v1.0 (G513QY.318 BIOS)AMD Renoir/Cezanne16GB512GB SAMSUNG MZVLQ512HBLU-00B00ASUS AMD Cezanne 512MB (2500/1000MHz)AMD Navi 21/23LQ156M1JW25Realtek RTL8111/8168/8411 + MEDIATEK MT7921 802.11ax PCIUbuntu 22.105.19.0-41-generic (x86_64)GNOME Shell 43.0X Server 1.21.1.4 + Wayland4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47)1.3.224GCC 12.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen Resolution5900hx Scikit Learn BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/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-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) - Platform Profile: balanced - CPU Microcode: 0xa50000c - ACPI Profile: balanced - Python 3.10.7- 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

abcResult OverviewPhoronix Test Suite100%101%101%102%Scikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnS.W.RTreeK.P.S.T.v.N.CPlot NeighborsH.G.B.C.OH.G.BMNIST DatasetText VectorizersK.P.S.T.v.N.SS.R.P.1.ITSNE MNIST DatasetC.D.BPlot Lasso PathPlot HierarchicalP.I.PH.G.B.H.BFeature ExpansionsP.P.K.AP.S.V.D2.N.L.RH.G.B.APlot WardSAGASGD RegressionLassoPlot OMP vs. LARSLocalOutlierFactorH.G.B.TGLMSparsify

5900hx scikit learnscikit-learn: Sample Without Replacementscikit-learn: Treescikit-learn: Kernel PCA Solvers / Time vs. N Componentsscikit-learn: Plot Neighborsscikit-learn: Hist Gradient Boosting Categorical Onlyscikit-learn: Hist Gradient Boostingscikit-learn: MNIST Datasetscikit-learn: Text Vectorizersscikit-learn: Kernel PCA Solvers / Time vs. N Samplesscikit-learn: Sparse Rand Projections / 100 Iterationsscikit-learn: TSNE MNIST Datasetscikit-learn: Covertype Dataset Benchmarkscikit-learn: Plot Lasso Pathscikit-learn: Plot Hierarchicalscikit-learn: Plot Incremental PCAscikit-learn: Hist Gradient Boosting Higgs Bosonscikit-learn: Feature Expansionsscikit-learn: Plot Polynomial Kernel Approximationscikit-learn: Plot Singular Value Decompositionscikit-learn: 20 Newsgroups / Logistic Regressionscikit-learn: Hist Gradient Boosting Adultscikit-learn: Plot Wardscikit-learn: SAGAscikit-learn: SGD Regressionscikit-learn: Lassoscikit-learn: Plot OMP vs. LARSscikit-learn: LocalOutlierFactorscikit-learn: Hist Gradient Boosting Threadingscikit-learn: GLMscikit-learn: Sparsifyscikit-learn: Glmnetabc119.67240.724169.270138.94615.72492.23659.28258.809193.448760.377236.977378.753196.189180.44334.62767.847134.561149.925135.59742.01771.04154.355732.860101.875430.672104.78659.868183.486406.904114.745122.69641.491170.439138.21815.71693.01059.96958.185193.399767.671235.418376.287194.416179.05934.86467.709133.854150.684136.27342.22571.04154.557733.048101.663430.417104.64359.985183.553407.075114.767120.90141.617172.701140.70815.93593.36659.80058.557195.460762.752237.618375.258194.465180.30734.77267.468134.335150.152136.19342.09570.75854.368735.468102.002431.810104.96559.969183.756406.724114.830OpenBenchmarking.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: Sample Without Replacementacb306090120150SE +/- 0.18, N = 3SE +/- 1.46, N = 3SE +/- 0.79, N = 3119.67120.90122.701. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Treeabc918273645SE +/- 0.44, N = 5SE +/- 0.36, N = 15SE +/- 0.41, N = 540.7241.4941.621. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Kernel PCA Solvers / Time vs. N Componentsabc4080120160200SE +/- 2.86, N = 12SE +/- 2.38, N = 12SE +/- 2.77, N = 12169.27170.44172.701. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Neighborsbac306090120150SE +/- 1.49, N = 3SE +/- 1.26, N = 3SE +/- 0.77, N = 3138.22138.95140.711. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Categorical Onlybac48121620SE +/- 0.08, N = 3SE +/- 0.08, N = 3SE +/- 0.18, N = 315.7215.7215.941. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boostingabc20406080100SE +/- 0.17, N = 3SE +/- 0.95, N = 3SE +/- 0.74, N = 392.2493.0193.371. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: MNIST Datasetacb1326395265SE +/- 0.07, N = 3SE +/- 0.08, N = 3SE +/- 0.13, N = 359.2859.8059.971. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Text Vectorizersbca1326395265SE +/- 0.07, N = 3SE +/- 0.14, N = 3SE +/- 0.02, N = 358.1958.5658.811. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Kernel PCA Solvers / Time vs. N Samplesbac4080120160200SE +/- 0.46, N = 3SE +/- 1.38, N = 3SE +/- 0.78, N = 3193.40193.45195.461. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparse Random Projections / 100 Iterationsacb170340510680850SE +/- 2.60, N = 3SE +/- 3.45, N = 3SE +/- 1.20, N = 3760.38762.75767.671. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: TSNE MNIST Datasetbac50100150200250SE +/- 0.31, N = 3SE +/- 0.39, N = 3SE +/- 0.31, N = 3235.42236.98237.621. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Covertype Dataset Benchmarkcba80160240320400SE +/- 0.82, N = 3SE +/- 0.57, N = 3SE +/- 1.06, N = 3375.26376.29378.751. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Lasso Pathbca4080120160200SE +/- 0.18, N = 3SE +/- 0.54, N = 3SE +/- 0.31, N = 3194.42194.47196.191. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Hierarchicalbca4080120160200SE +/- 0.37, N = 3SE +/- 0.84, N = 3SE +/- 0.21, N = 3179.06180.31180.441. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Incremental PCAacb816243240SE +/- 0.14, N = 3SE +/- 0.34, N = 6SE +/- 0.50, N = 334.6334.7734.861. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Higgs Bosoncba1530456075SE +/- 0.02, N = 3SE +/- 0.18, N = 3SE +/- 0.07, N = 367.4767.7167.851. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Feature Expansionsbca306090120150SE +/- 0.21, N = 3SE +/- 0.04, N = 3SE +/- 0.35, N = 3133.85134.34134.561. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Polynomial Kernel Approximationacb306090120150SE +/- 0.18, N = 3SE +/- 0.07, N = 3SE +/- 0.38, N = 3149.93150.15150.681. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Singular Value Decompositionacb306090120150SE +/- 0.16, N = 3SE +/- 0.42, N = 3SE +/- 0.11, N = 3135.60136.19136.271. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: 20 Newsgroups / Logistic Regressionacb1020304050SE +/- 0.14, N = 3SE +/- 0.06, N = 3SE +/- 0.17, N = 342.0242.1042.231. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Adultcab1632486480SE +/- 0.08, N = 3SE +/- 0.07, N = 3SE +/- 0.30, N = 370.7671.0471.041. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Wardacb1224364860SE +/- 0.29, N = 3SE +/- 0.04, N = 3SE +/- 0.18, N = 354.3654.3754.561. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SAGAabc160320480640800SE +/- 6.30, N = 3SE +/- 1.92, N = 3SE +/- 0.31, N = 3732.86733.05735.471. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGD Regressionbac20406080100SE +/- 0.16, N = 3SE +/- 0.26, N = 3SE +/- 0.25, N = 3101.66101.88102.001. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Lassobac90180270360450SE +/- 0.98, N = 3SE +/- 0.52, N = 3SE +/- 0.43, N = 3430.42430.67431.811. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot OMP vs. LARSbac20406080100SE +/- 0.08, N = 3SE +/- 0.21, N = 3SE +/- 0.24, N = 3104.64104.79104.971. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: LocalOutlierFactoracb1326395265SE +/- 0.64, N = 3SE +/- 0.24, N = 3SE +/- 0.58, N = 359.8759.9759.991. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Threadingabc4080120160200SE +/- 0.15, N = 3SE +/- 0.23, N = 3SE +/- 0.21, N = 3183.49183.55183.761. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: GLMcab90180270360450SE +/- 0.54, N = 3SE +/- 2.13, N = 3SE +/- 0.79, N = 3406.72406.90407.081. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparsifyabc306090120150SE +/- 0.50, N = 3SE +/- 0.20, N = 3SE +/- 0.14, N = 3114.75114.77114.831. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

Benchmark: Plot Non-Negative Matrix Factorization

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

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

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

Benchmark: Isotonic / Perturbed Logarithm

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

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

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

Benchmark: RCV1 Logreg Convergencet

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

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

c: 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.

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

c: 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

b: 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

c: 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: Isotonic / Logistic

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

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

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

Benchmark: Plot Fast KMeans

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

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

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

Benchmark: Isolation Forest

a: The test quit with a non-zero exit status. E: OSError: The cache for fetch_kddcup99 is invalid, please delete /home/phoronix/scikit_learn_data/kddcup99-py3 and run the fetch_kddcup99 again

b: The test quit with a non-zero exit status. E: OSError: The cache for fetch_kddcup99 is invalid, please delete /home/phoronix/scikit_learn_data/kddcup99-py3 and run the fetch_kddcup99 again

c: The test quit with a non-zero exit status. E: OSError: The cache for fetch_kddcup99 is invalid, please delete /home/phoronix/scikit_learn_data/kddcup99-py3 and run the fetch_kddcup99 again

Benchmark: SGDOneClassSVM

a: The test quit with a non-zero exit status. E: OSError: The cache for fetch_kddcup99 is invalid, please delete /home/phoronix/scikit_learn_data/kddcup99-py3 and run the fetch_kddcup99 again

b: The test quit with a non-zero exit status. E: OSError: The cache for fetch_kddcup99 is invalid, please delete /home/phoronix/scikit_learn_data/kddcup99-py3 and run the fetch_kddcup99 again

c: The test quit with a non-zero exit status. E: OSError: The cache for fetch_kddcup99 is invalid, please delete /home/phoronix/scikit_learn_data/kddcup99-py3 and run the fetch_kddcup99 again

Benchmark: Glmnet

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

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

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