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.
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phoronix-test-suite benchmark 2305115-NE-SCIKITLEA14 scikit learn 5950X - Phoronix Test Suite 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&grt&sor .
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: GLM scikit-learn: SAGA scikit-learn: Tree scikit-learn: Lasso scikit-learn: Sparsify scikit-learn: Plot Ward scikit-learn: MNIST Dataset scikit-learn: Plot Neighbors scikit-learn: SGD Regression scikit-learn: SGDOneClassSVM scikit-learn: Plot Lasso Path scikit-learn: Isolation Forest scikit-learn: Plot Fast KMeans scikit-learn: Text Vectorizers scikit-learn: Plot Hierarchical scikit-learn: Plot OMP vs. LARS scikit-learn: Feature Expansions scikit-learn: LocalOutlierFactor scikit-learn: TSNE MNIST Dataset scikit-learn: Isotonic / Logistic scikit-learn: Plot Incremental PCA scikit-learn: Hist Gradient Boosting scikit-learn: Sample Without Replacement scikit-learn: Covertype Dataset Benchmark scikit-learn: Hist Gradient Boosting Adult scikit-learn: Hist Gradient Boosting Threading scikit-learn: Plot Singular Value Decomposition scikit-learn: Hist Gradient Boosting Higgs Boson scikit-learn: 20 Newsgroups / Logistic Regression scikit-learn: Plot Polynomial Kernel Approximation scikit-learn: Hist Gradient Boosting Categorical Only scikit-learn: Kernel PCA Solvers / Time vs. N Samples scikit-learn: Kernel PCA Solvers / Time vs. N Components scikit-learn: Sparse Rand Projections / 100 Iterations a b c 167.138 568.364 34.484 309.792 67.557 33.772 42.813 103.854 79.631 238.929 112.273 168.473 123.579 39.491 115.026 52.051 79.061 23.360 141.755 1020.783 47.942 88.836 65.763 270.853 84.066 65.386 44.701 31.812 24.632 92.657 15.829 83.710 34.331 381.423 142.180 571.019 35.373 208.539 67.552 33.815 42.453 102.510 58.841 204.919 123.748 171.268 125.401 39.506 114.506 33.088 79.481 23.386 142.709 1015.238 47.115 89.008 65.591 270.399 84.648 66.505 44.875 32.731 24.589 93.012 15.937 85.351 33.961 378.067 141.992 569.637 34.747 208.917 67.939 34.178 42.834 104.838 59.164 208.572 125.345 173.116 124.308 39.920 114.279 33.414 80.573 23.482 144.040 1022.454 45.343 89.488 65.308 271.991 83.208 65.368 44.802 32.450 25.179 93.022 15.807 86.727 35.192 379.121 OpenBenchmarking.org
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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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 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 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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 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: 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: 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: 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
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: 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: 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
Phoronix Test Suite v10.8.4