scikit learn 5950X AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG CROSSHAIR X670E HERO (1101 BIOS) and AMD Radeon RX 7900 XTX 24GB on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2305115-NE-SCIKITLEA14&sor&grr .
scikit learn 5950X Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution a b c AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads) ASUS ROG CROSSHAIR X670E HERO (1101 BIOS) AMD Device 14d8 32GB 2048GB SOLIDIGM SSDPFKKW020X7 + 2000GB AMD Radeon RX 7900 XTX 24GB (2304/1249MHz) AMD Device ab30 ASUS MG28U Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 Ubuntu 22.04 6.3.0-060300rc7daily20230417-generic (x86_64) GNOME Shell 42.5 X Server 1.21.1.3 + Wayland 4.6 Mesa 23.2.0-devel (git-f6fb189 2023-04-18 jammy-oibaf-ppa) (LLVM 15.0.7 DRM 3.52) 1.3.246 GCC 11.3.0 ext4 3840x2160 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --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 Processor Details - Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa601203 Python Details - Python 3.10.6 Security Details - 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 Enhanced / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
scikit learn 5950X scikit-learn: Isotonic / Logistic scikit-learn: SAGA scikit-learn: Sparse Rand Projections / 100 Iterations scikit-learn: Kernel PCA Solvers / Time vs. N Samples scikit-learn: Covertype Dataset Benchmark scikit-learn: SGDOneClassSVM scikit-learn: Lasso scikit-learn: Plot Incremental PCA scikit-learn: Isolation Forest scikit-learn: TSNE MNIST Dataset scikit-learn: GLM scikit-learn: Tree scikit-learn: Kernel PCA Solvers / Time vs. N Components scikit-learn: Plot Fast KMeans scikit-learn: Hist Gradient Boosting Higgs Boson scikit-learn: Plot Lasso Path scikit-learn: Plot Hierarchical scikit-learn: Plot Neighbors scikit-learn: Plot Polynomial Kernel Approximation scikit-learn: Plot Singular Value Decomposition scikit-learn: Hist Gradient Boosting scikit-learn: Hist Gradient Boosting Adult scikit-learn: Feature Expansions scikit-learn: Sparsify scikit-learn: SGD Regression scikit-learn: Hist Gradient Boosting Threading scikit-learn: Sample Without Replacement scikit-learn: MNIST Dataset scikit-learn: Text Vectorizers scikit-learn: Plot OMP vs. LARS scikit-learn: Plot Ward scikit-learn: 20 Newsgroups / Logistic Regression scikit-learn: LocalOutlierFactor scikit-learn: Hist Gradient Boosting Categorical Only scikit-learn: Glmnet a b c 1020.783 568.364 381.423 83.710 270.853 238.929 309.792 47.942 168.473 141.755 167.138 34.484 34.331 123.579 31.812 112.273 115.026 103.854 92.657 44.701 88.836 84.066 79.061 67.557 79.631 65.386 65.763 42.813 39.491 52.051 33.772 24.632 23.360 15.829 1015.238 571.019 378.067 85.351 270.399 204.919 208.539 47.115 171.268 142.709 142.180 35.373 33.961 125.401 32.731 123.748 114.506 102.510 93.012 44.875 89.008 84.648 79.481 67.552 58.841 66.505 65.591 42.453 39.506 33.088 33.815 24.589 23.386 15.937 1022.454 569.637 379.121 86.727 271.991 208.572 208.917 45.343 173.116 144.040 141.992 34.747 35.192 124.308 32.450 125.345 114.279 104.838 93.022 44.802 89.488 83.208 80.573 67.939 59.164 65.368 65.308 42.834 39.920 33.414 34.178 25.179 23.482 15.807 OpenBenchmarking.org
Scikit-Learn Benchmark: Isotonic / Logistic OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Isotonic / Logistic b a c 200 400 600 800 1000 SE +/- 0.65, N = 3 SE +/- 5.97, N = 3 SE +/- 2.35, N = 3 1015.24 1020.78 1022.45 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: SAGA OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SAGA a c b 120 240 360 480 600 SE +/- 2.25, N = 3 SE +/- 1.46, N = 3 SE +/- 3.47, N = 3 568.36 569.64 571.02 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Sparse Random Projections / 100 Iterations OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Sparse Random Projections / 100 Iterations b c a 80 160 240 320 400 SE +/- 0.26, N = 3 SE +/- 0.62, N = 3 SE +/- 2.15, N = 3 378.07 379.12 381.42 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Kernel PCA Solvers / Time vs. N Samples OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Kernel PCA Solvers / Time vs. N Samples a b c 20 40 60 80 100 SE +/- 2.28, N = 12 SE +/- 1.27, N = 15 SE +/- 1.74, N = 15 83.71 85.35 86.73 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Covertype Dataset Benchmark OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Covertype Dataset Benchmark b a c 60 120 180 240 300 SE +/- 0.09, N = 3 SE +/- 1.22, N = 3 SE +/- 1.29, N = 3 270.40 270.85 271.99 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: SGDOneClassSVM OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SGDOneClassSVM b c a 50 100 150 200 250 SE +/- 0.37, N = 3 SE +/- 2.09, N = 5 SE +/- 0.51, N = 3 204.92 208.57 238.93 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Lasso OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Lasso b c a 70 140 210 280 350 SE +/- 0.81, N = 3 SE +/- 1.28, N = 3 SE +/- 0.34, N = 3 208.54 208.92 309.79 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Incremental PCA OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Incremental PCA c b a 11 22 33 44 55 SE +/- 1.03, N = 15 SE +/- 0.78, N = 15 SE +/- 0.72, N = 15 45.34 47.12 47.94 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Isolation Forest OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Isolation Forest a b c 40 80 120 160 200 SE +/- 0.26, N = 3 SE +/- 0.30, N = 3 SE +/- 1.54, N = 3 168.47 171.27 173.12 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: TSNE MNIST Dataset OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: TSNE MNIST Dataset a b c 30 60 90 120 150 SE +/- 1.56, N = 5 SE +/- 0.37, N = 3 SE +/- 0.84, N = 3 141.76 142.71 144.04 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: GLM OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: GLM c b a 40 80 120 160 200 SE +/- 0.73, N = 3 SE +/- 0.63, N = 3 SE +/- 0.97, N = 3 141.99 142.18 167.14 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Tree OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Tree a c b 8 16 24 32 40 SE +/- 0.43, N = 15 SE +/- 0.43, N = 15 SE +/- 0.38, N = 15 34.48 34.75 35.37 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Kernel PCA Solvers / Time vs. N Components OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Kernel PCA Solvers / Time vs. N Components b a c 8 16 24 32 40 SE +/- 0.59, N = 15 SE +/- 0.52, N = 15 SE +/- 0.52, N = 15 33.96 34.33 35.19 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Fast KMeans OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Fast KMeans a c b 30 60 90 120 150 SE +/- 0.29, N = 3 SE +/- 0.61, N = 3 SE +/- 0.83, N = 3 123.58 124.31 125.40 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Hist Gradient Boosting Higgs Boson OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Higgs Boson a c b 8 16 24 32 40 SE +/- 0.26, N = 3 SE +/- 0.15, N = 3 SE +/- 0.23, N = 3 31.81 32.45 32.73 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Lasso Path OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Lasso Path a b c 30 60 90 120 150 SE +/- 0.58, N = 3 SE +/- 0.89, N = 3 SE +/- 0.63, N = 3 112.27 123.75 125.35 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Hierarchical OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Hierarchical c b a 30 60 90 120 150 SE +/- 0.41, N = 3 SE +/- 0.15, N = 3 SE +/- 0.26, N = 3 114.28 114.51 115.03 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Neighbors OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Neighbors b a c 20 40 60 80 100 SE +/- 1.07, N = 3 SE +/- 0.38, N = 3 SE +/- 0.52, N = 3 102.51 103.85 104.84 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Polynomial Kernel Approximation OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Polynomial Kernel Approximation a b c 20 40 60 80 100 SE +/- 0.11, N = 3 SE +/- 0.28, N = 3 SE +/- 0.42, N = 3 92.66 93.01 93.02 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Singular Value Decomposition OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Singular Value Decomposition a c b 10 20 30 40 50 SE +/- 0.46, N = 15 SE +/- 0.52, N = 3 SE +/- 0.38, N = 3 44.70 44.80 44.88 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Hist Gradient Boosting OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting a b c 20 40 60 80 100 SE +/- 0.73, N = 3 SE +/- 0.58, N = 3 SE +/- 0.49, N = 3 88.84 89.01 89.49 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Hist Gradient Boosting Adult OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Adult c a b 20 40 60 80 100 SE +/- 0.32, N = 3 SE +/- 0.38, N = 3 SE +/- 0.69, N = 3 83.21 84.07 84.65 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Feature Expansions OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Feature Expansions a b c 20 40 60 80 100 SE +/- 0.33, N = 3 SE +/- 0.12, N = 3 SE +/- 0.47, N = 3 79.06 79.48 80.57 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Sparsify OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Sparsify b a c 15 30 45 60 75 SE +/- 0.56, N = 3 SE +/- 0.71, N = 3 SE +/- 0.72, N = 3 67.55 67.56 67.94 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: SGD Regression OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SGD Regression b c a 20 40 60 80 100 SE +/- 0.13, N = 3 SE +/- 0.12, N = 3 SE +/- 0.29, N = 3 58.84 59.16 79.63 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Hist Gradient Boosting Threading OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Threading c a b 15 30 45 60 75 SE +/- 0.28, N = 3 SE +/- 0.31, N = 3 SE +/- 0.52, N = 3 65.37 65.39 66.51 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Sample Without Replacement OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Sample Without Replacement c b a 15 30 45 60 75 SE +/- 0.43, N = 3 SE +/- 0.34, N = 3 SE +/- 0.03, N = 3 65.31 65.59 65.76 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: MNIST Dataset OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: MNIST Dataset b a c 10 20 30 40 50 SE +/- 0.01, N = 3 SE +/- 0.27, N = 3 SE +/- 0.22, N = 3 42.45 42.81 42.83 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Text Vectorizers OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Text Vectorizers a b c 9 18 27 36 45 SE +/- 0.14, N = 3 SE +/- 0.08, N = 3 SE +/- 0.22, N = 3 39.49 39.51 39.92 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot OMP vs. LARS OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot OMP vs. LARS b c a 12 24 36 48 60 SE +/- 0.09, N = 3 SE +/- 0.14, N = 3 SE +/- 0.38, N = 3 33.09 33.41 52.05 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Ward OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Ward a b c 8 16 24 32 40 SE +/- 0.05, N = 3 SE +/- 0.42, N = 3 SE +/- 0.28, N = 3 33.77 33.82 34.18 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: 20 Newsgroups / Logistic Regression OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: 20 Newsgroups / Logistic Regression b a c 6 12 18 24 30 SE +/- 0.20, N = 3 SE +/- 0.32, N = 3 SE +/- 0.21, N = 3 24.59 24.63 25.18 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: LocalOutlierFactor OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: LocalOutlierFactor a b c 6 12 18 24 30 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 23.36 23.39 23.48 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Hist Gradient Boosting Categorical Only OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Categorical Only c a b 4 8 12 16 20 SE +/- 0.01, N = 3 SE +/- 0.13, N = 3 SE +/- 0.14, N = 3 15.81 15.83 15.94 1. (F9X) gfortran options: -O0
Phoronix Test Suite v10.8.5