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: GLMscikit-learn: SAGAscikit-learn: Treescikit-learn: Lassoscikit-learn: Sparsifyscikit-learn: Plot Wardscikit-learn: MNIST Datasetscikit-learn: Plot Neighborsscikit-learn: SGD Regressionscikit-learn: Plot Lasso Pathscikit-learn: Text Vectorizersscikit-learn: Plot Hierarchicalscikit-learn: Plot OMP vs. LARSscikit-learn: Feature Expansionsscikit-learn: LocalOutlierFactorscikit-learn: TSNE MNIST Datasetscikit-learn: Plot Incremental PCAscikit-learn: Hist Gradient Boostingscikit-learn: Sample Without Replacementscikit-learn: Covertype Dataset Benchmarkscikit-learn: Hist Gradient Boosting Adultscikit-learn: Hist Gradient Boosting Threadingscikit-learn: Plot Singular Value Decompositionscikit-learn: Hist Gradient Boosting Higgs Bosonscikit-learn: 20 Newsgroups / Logistic Regressionscikit-learn: Plot Polynomial Kernel Approximationscikit-learn: Hist Gradient Boosting Categorical Onlyscikit-learn: Kernel PCA Solvers / Time vs. N Samplesscikit-learn: Kernel PCA Solvers / Time vs. N Componentsscikit-learn: Sparse Rand Projections / 100 Iterationsabc406.904732.86040.724430.672114.74554.35559.282138.946101.875196.18958.809180.443104.786134.56159.868236.97734.62792.236119.672378.75371.041183.486135.59767.84742.017149.92515.724193.448169.270760.377407.075733.04841.491430.417114.76754.55759.969138.218101.663194.41658.185179.059104.643133.85459.985235.41834.86493.010122.696376.28771.041183.553136.27367.70942.225150.68415.716193.399170.439767.671406.724735.46841.617431.810114.83054.36859.800140.708102.002194.46558.557180.307104.965134.33559.969237.61834.77293.366120.901375.25870.758183.756136.19367.46842.095150.15215.935195.460172.701762.752OpenBenchmarking.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: GLMcba90180270360450SE +/- 0.54, N = 3SE +/- 0.79, N = 3SE +/- 2.13, N = 3406.72407.08406.901. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SAGAcba160320480640800SE +/- 0.31, N = 3SE +/- 1.92, N = 3SE +/- 6.30, N = 3735.47733.05732.861. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Treecba918273645SE +/- 0.41, N = 5SE +/- 0.36, N = 15SE +/- 0.44, N = 541.6241.4940.721. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Lassocba90180270360450SE +/- 0.43, N = 3SE +/- 0.98, N = 3SE +/- 0.52, N = 3431.81430.42430.671. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

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'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparsifycba306090120150SE +/- 0.14, N = 3SE +/- 0.20, N = 3SE +/- 0.50, N = 3114.83114.77114.751. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Wardcba1224364860SE +/- 0.04, N = 3SE +/- 0.18, N = 3SE +/- 0.29, N = 354.3754.5654.361. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: MNIST Datasetcba1326395265SE +/- 0.08, N = 3SE +/- 0.13, N = 3SE +/- 0.07, N = 359.8059.9759.281. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Neighborscba306090120150SE +/- 0.77, N = 3SE +/- 1.49, N = 3SE +/- 1.26, N = 3140.71138.22138.951. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGD Regressioncba20406080100SE +/- 0.25, N = 3SE +/- 0.16, N = 3SE +/- 0.26, N = 3102.00101.66101.881. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

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

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Lasso Pathcba4080120160200SE +/- 0.54, N = 3SE +/- 0.18, N = 3SE +/- 0.31, N = 3194.47194.42196.191. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

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: 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.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Text Vectorizerscba1326395265SE +/- 0.14, N = 3SE +/- 0.07, N = 3SE +/- 0.02, N = 358.5658.1958.811. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Hierarchicalcba4080120160200SE +/- 0.84, N = 3SE +/- 0.37, N = 3SE +/- 0.21, N = 3180.31179.06180.441. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot OMP vs. LARScba20406080100SE +/- 0.24, N = 3SE +/- 0.08, N = 3SE +/- 0.21, N = 3104.97104.64104.791. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Feature Expansionscba306090120150SE +/- 0.04, N = 3SE +/- 0.21, N = 3SE +/- 0.35, N = 3134.34133.85134.561. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: LocalOutlierFactorcba1326395265SE +/- 0.24, N = 3SE +/- 0.58, N = 3SE +/- 0.64, N = 359.9759.9959.871. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: TSNE MNIST Datasetcba50100150200250SE +/- 0.31, N = 3SE +/- 0.31, N = 3SE +/- 0.39, N = 3237.62235.42236.981. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

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.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Incremental PCAcba816243240SE +/- 0.34, N = 6SE +/- 0.50, N = 3SE +/- 0.14, N = 334.7734.8634.631. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boostingcba20406080100SE +/- 0.74, N = 3SE +/- 0.95, N = 3SE +/- 0.17, N = 393.3793.0192.241. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

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 / 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: 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

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sample Without Replacementcba306090120150SE +/- 1.46, N = 3SE +/- 0.79, N = 3SE +/- 0.18, N = 3120.90122.70119.671. (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: Hist Gradient Boosting Adultcba1632486480SE +/- 0.08, N = 3SE +/- 0.30, N = 3SE +/- 0.07, N = 370.7671.0471.041. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

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.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Threadingcba4080120160200SE +/- 0.21, N = 3SE +/- 0.23, N = 3SE +/- 0.15, N = 3183.76183.55183.491. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Singular Value Decompositioncba306090120150SE +/- 0.42, N = 3SE +/- 0.11, N = 3SE +/- 0.16, N = 3136.19136.27135.601. (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: 20 Newsgroups / Logistic Regressioncba1020304050SE +/- 0.06, N = 3SE +/- 0.17, N = 3SE +/- 0.14, N = 342.1042.2342.021. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Polynomial Kernel Approximationcba306090120150SE +/- 0.07, N = 3SE +/- 0.38, N = 3SE +/- 0.18, N = 3150.15150.68149.931. (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:

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Categorical Onlycba48121620SE +/- 0.18, N = 3SE +/- 0.08, N = 3SE +/- 0.08, N = 315.9415.7215.721. (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 Samplescba4080120160200SE +/- 0.78, N = 3SE +/- 0.46, N = 3SE +/- 1.38, N = 3195.46193.40193.451. (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 Componentscba4080120160200SE +/- 2.77, N = 12SE +/- 2.38, N = 12SE +/- 2.86, N = 12172.70170.44169.271. (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 Iterationscba170340510680850SE +/- 3.45, N = 3SE +/- 1.20, N = 3SE +/- 2.60, N = 3762.75767.67760.381. (F9X) gfortran options: -O3 -fopenmp -fno-tree-vectorize -lm -lpthread -lgfortran -lc