SCIKIT-leaRn tests

AMD Ryzen 9 3900X 12-Core testing with a MSI X570-A PRO (MS-7C37) v3.0 (H.70 BIOS) and NVIDIA GeForce RTX 3060 on Ubuntu 24.04 via the Phoronix Test Suite. Noble python 3.12 performance vs. python compiled without frame pointers.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2405056-VPA1-MERGE7223
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noble
May 02
  12 Hours, 54 Minutes
scikit-learn-python-disabled-fp
May 03
  10 Hours, 58 Minutes
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SCIKIT-leaRn testsOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 3900X 12-Core @ 3.80GHz (12 Cores / 24 Threads)MSI X570-A PRO (MS-7C37) v3.0 (H.70 BIOS)AMD Starship/Matisse2 x 16GB DDR4-3200MT/s F4-3200C16-16GVK2000GB Seagate ST2000DM006-2DM1 + 2000GB Western Digital WD20EZAZ-00G + 500GB Samsung SSD 860 + 8002GB Seagate ST8000DM004-2CX1 + 1000GB CT1000BX500SSD1 + 512GB TS512GESD310CNVIDIA GeForce RTX 3060NVIDIA GA104 HD AudioDELL P2314H + U32J59xRealtek RTL8111/8168/8211/8411Ubuntu 24.046.8.0-31-generic (x86_64)GCC 13.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelCompilerFile-SystemScreen ResolutionSCIKIT-leaRn Tests PerformanceSystem Logs- Transparent Huge Pages: madvise- noble: --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-backtrace --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-13-uJ7kn6/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-uJ7kn6/gcc-13-13.2.0/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 - scikit-learn-python-disabled-fp: --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-backtrace --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-13-S2PGXz/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-S2PGXz/gcc-13-13.2.0/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) - CPU Microcode: 0x8701013- Python 3.12.3- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of Safe RET + 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; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected

noble vs. scikit-learn-python-disabled-fp ComparisonPhoronix Test SuiteBaseline+1.1%+1.1%+2.2%+2.2%+3.3%+3.3%+4.4%+4.4%4.4%4.2%3.7%3.6%3.6%TreeS.W.RSGDOneClassSVMSGD RegressionText VectorizersI.P.L2%Scikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-LearnScikit-Learnnoblescikit-learn-python-disabled-fp

SCIKIT-leaRn testsscikit-learn: Treescikit-learn: Sample Without Replacementscikit-learn: Text Vectorizersscikit-learn: Isotonic / Perturbed Logarithmscikit-learn: TSNE MNIST Datasetscikit-learn: Plot Polynomial Kernel Approximationscikit-learn: Sparse Rand Projections / 100 Iterationsscikit-learn: Kernel PCA Solvers / Time vs. N Componentsscikit-learn: Hist Gradient Boostingscikit-learn: Plot Hierarchicalscikit-learn: Hist Gradient Boosting Categorical Onlyscikit-learn: Hist Gradient Boosting Adultscikit-learn: Isolation Forestscikit-learn: SAGAscikit-learn: GLMscikit-learn: Isotonic / Logisticscikit-learn: Plot Singular Value Decompositionscikit-learn: Sparsifyscikit-learn: Lassoscikit-learn: Plot Incremental PCAscikit-learn: MNIST Datasetscikit-learn: LocalOutlierFactorscikit-learn: 20 Newsgroups / Logistic Regressionscikit-learn: Plot Wardscikit-learn: Hist Gradient Boosting Threadingscikit-learn: Feature Expansionsscikit-learn: Plot OMP vs. LARSscikit-learn: Hist Gradient Boosting Higgs Bosonscikit-learn: Plot Fast KMeansscikit-learn: Covertype Dataset Benchmarkscikit-learn: Plot Neighborsscikit-learn: Plot Lasso Pathscikit-learn: Kernel PCA Solvers / Time vs. N Samplesscikit-learn: SGDOneClassSVMscikit-learn: SGD Regressionscikit-learn: Glmnetnoblescikit-learn-python-disabled-fp48.325180.10565.7401787.711259.758155.494557.98570.231117.089207.11520.053111.830300.663873.257282.6761435.27396.614130.297351.023102.78665.70653.38837.58853.990111.843135.12170.08761.363172.977375.954144.444232.397266.450328.93883.04546.295172.81963.4801824.299254.864152.597566.95169.159115.39204.13119.796110.399304.156863.605279.6361420.39195.658129.055347.803101.85165.17153.00537.80454.227111.377135.64169.83561.165172.641375.460144.301232.343266.465317.25580.147OpenBenchmarking.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: Treenoblescikit-learn-python-disabled-fp1122334455SE +/- 0.53, N = 15SE +/- 0.65, N = 348.3346.301. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sample Without Replacementnoblescikit-learn-python-disabled-fp4080120160200SE +/- 1.97, N = 3SE +/- 2.35, N = 3180.11172.821. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Text Vectorizersnoblescikit-learn-python-disabled-fp1530456075SE +/- 0.04, N = 3SE +/- 0.34, N = 365.7463.481. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isotonic / Perturbed Logarithmscikit-learn-python-disabled-fpnoble400800120016002000SE +/- 12.01, N = 3SE +/- 2.41, N = 31824.301787.711. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: TSNE MNIST Datasetnoblescikit-learn-python-disabled-fp60120180240300SE +/- 1.20, N = 3SE +/- 0.80, N = 3259.76254.861. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Polynomial Kernel Approximationnoblescikit-learn-python-disabled-fp306090120150SE +/- 0.93, N = 3SE +/- 0.38, N = 3155.49152.601. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparse Random Projections / 100 Iterationsscikit-learn-python-disabled-fpnoble120240360480600SE +/- 7.45, N = 3SE +/- 2.85, N = 3566.95557.991. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Kernel PCA Solvers / Time vs. N Componentsnoblescikit-learn-python-disabled-fp1632486480SE +/- 0.61, N = 8SE +/- 0.34, N = 370.2369.161. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boostingnoblescikit-learn-python-disabled-fp306090120150SE +/- 0.39, N = 3SE +/- 0.19, N = 3117.09115.391. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Hierarchicalnoblescikit-learn-python-disabled-fp50100150200250SE +/- 1.82, N = 3SE +/- 1.58, N = 3207.12204.131. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Categorical Onlynoblescikit-learn-python-disabled-fp510152025SE +/- 0.12, N = 3SE +/- 0.09, N = 320.0519.801. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Adultnoblescikit-learn-python-disabled-fp306090120150SE +/- 0.14, N = 3SE +/- 0.40, N = 3111.83110.401. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isolation Forestscikit-learn-python-disabled-fpnoble70140210280350SE +/- 3.58, N = 3SE +/- 2.33, N = 3304.16300.661. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SAGAnoblescikit-learn-python-disabled-fp2004006008001000SE +/- 10.17, N = 4SE +/- 11.43, N = 3873.26863.611. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: GLMnoblescikit-learn-python-disabled-fp60120180240300SE +/- 2.42, N = 8SE +/- 3.95, N = 3282.68279.641. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isotonic / Logisticnoblescikit-learn-python-disabled-fp30060090012001500SE +/- 3.15, N = 3SE +/- 15.77, N = 31435.271420.391. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Singular Value Decompositionnoblescikit-learn-python-disabled-fp20406080100SE +/- 0.67, N = 3SE +/- 0.55, N = 396.6195.661. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparsifynoblescikit-learn-python-disabled-fp306090120150SE +/- 1.56, N = 3SE +/- 1.16, N = 7130.30129.061. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Lassonoblescikit-learn-python-disabled-fp80160240320400SE +/- 2.06, N = 3SE +/- 1.29, N = 3351.02347.801. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Incremental PCAnoblescikit-learn-python-disabled-fp20406080100SE +/- 0.45, N = 3SE +/- 0.24, N = 3102.79101.851. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: MNIST Datasetnoblescikit-learn-python-disabled-fp1530456075SE +/- 0.42, N = 3SE +/- 0.76, N = 365.7165.171. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: LocalOutlierFactornoblescikit-learn-python-disabled-fp1224364860SE +/- 0.10, N = 3SE +/- 0.19, N = 353.3953.011. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: 20 Newsgroups / Logistic Regressionscikit-learn-python-disabled-fpnoble918273645SE +/- 0.16, N = 3SE +/- 0.16, N = 337.8037.591. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Wardscikit-learn-python-disabled-fpnoble1224364860SE +/- 0.66, N = 3SE +/- 0.59, N = 554.2353.991. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Threadingnoblescikit-learn-python-disabled-fp306090120150SE +/- 0.28, N = 3SE +/- 0.03, N = 3111.84111.381. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Feature Expansionsscikit-learn-python-disabled-fpnoble306090120150SE +/- 1.29, N = 3SE +/- 0.89, N = 3135.64135.121. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot OMP vs. LARSnoblescikit-learn-python-disabled-fp1632486480SE +/- 0.22, N = 3SE +/- 0.20, N = 370.0969.841. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Higgs Bosonnoblescikit-learn-python-disabled-fp1428425670SE +/- 0.02, N = 3SE +/- 0.34, N = 361.3661.171. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Fast KMeansnoblescikit-learn-python-disabled-fp4080120160200SE +/- 0.83, N = 3SE +/- 0.39, N = 3172.98172.641. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Covertype Dataset Benchmarknoblescikit-learn-python-disabled-fp80160240320400SE +/- 3.40, N = 3SE +/- 5.29, N = 3375.95375.461. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Neighborsnoblescikit-learn-python-disabled-fp306090120150SE +/- 1.68, N = 3SE +/- 1.18, N = 3144.44144.301. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Lasso Pathnoblescikit-learn-python-disabled-fp50100150200250SE +/- 0.17, N = 3SE +/- 0.91, N = 3232.40232.341. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Kernel PCA Solvers / Time vs. N Samplesscikit-learn-python-disabled-fpnoble60120180240300SE +/- 0.65, N = 3SE +/- 1.59, N = 3266.47266.451. (F9X) gfortran options: -O0

Benchmark: Plot Non-Negative Matrix Factorization

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

scikit-learn-python-disabled-fp: The test quit with a non-zero exit status. E: KeyError:

Benchmark: RCV1 Logreg Convergencet

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

scikit-learn-python-disabled-fp: The test quit with a non-zero exit status. E: IndexError: list index out of range

Benchmark: Isotonic / Pathological

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

scikit-learn-python-disabled-fp: The test quit with a non-zero exit status.

Benchmark: Plot Parallel Pairwise

noble: 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

scikit-learn-python-disabled-fp: 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

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGDOneClassSVMnoblescikit-learn-python-disabled-fp70140210280350SE +/- 9.62, N = 9SE +/- 3.04, N = 3328.94317.261. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGD Regressionnoblescikit-learn-python-disabled-fp20406080100SE +/- 1.86, N = 15SE +/- 1.15, N = 383.0580.151. (F9X) gfortran options: -O0

Benchmark: Glmnet

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

scikit-learn-python-disabled-fp: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'glmnet'