Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2406248-NE-C6I4XLARG35 c6i.4xlarge - Phoronix Test Suite c6i.4xlarge c6i.4xlarge
HTML result view exported from: https://openbenchmarking.org/result/2406248-NE-C6I4XLARG35&rdt&grs .
c6i.4xlarge Processor Motherboard Chipset Memory Disk Graphics Network OS Kernel Vulkan Compiler File-System Screen Resolution System Layer c6i.4xlarge Intel Xeon Platinum 8375C - EFI VGA - Amazon EC2 Intel Xeon Platinum 8375C (8 Cores / 16 Threads) Amazon EC2 c6i.4xlarge (1.0 BIOS) Intel 440FX 82441FX PMC 1 x 32 GB DDR4-3200MT/s 215GB Amazon Elastic Block Store EFI VGA Amazon Elastic Ubuntu 22.04 6.5.0-1020-aws (x86_64) 1.3.255 GCC 11.4.0 ext4 800x600 amazon 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-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/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 - CPU Microcode: 0xd0003d1 Python Details - Python 3.11.9 Security Details - gather_data_sampling: Unknown: Dependent on hypervisor status + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT Host state unknown + retbleed: Not affected + spec_rstack_overflow: 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: SW sequence; BHI: Syscall hardening KVM: SW loop + srbds: Not affected + tsx_async_abort: Not affected
c6i.4xlarge scikit-learn: 20 Newsgroups / Logistic Regression onednn: Recurrent Neural Network Inference - CPU onednn: Recurrent Neural Network Training - CPU onednn: Deconvolution Batch shapes_3d - CPU onednn: IP Shapes 3D - CPU onednn: IP Shapes 1D - CPU onednn: Convolution Batch Shapes Auto - CPU scikit-learn: Sparse Rand Projections / 100 Iterations scikit-learn: Kernel PCA Solvers / Time vs. N Components scikit-learn: Kernel PCA Solvers / Time vs. N Samples scikit-learn: Hist Gradient Boosting Categorical Only scikit-learn: Plot Polynomial Kernel Approximation scikit-learn: Hist Gradient Boosting Higgs Boson scikit-learn: Plot Singular Value Decomposition scikit-learn: Hist Gradient Boosting Threading scikit-learn: Isotonic / Perturbed Logarithm scikit-learn: Hist Gradient Boosting Adult scikit-learn: Covertype Dataset Benchmark scikit-learn: Sample Without Replacement scikit-learn: Hist Gradient Boosting scikit-learn: Plot Incremental PCA scikit-learn: Isotonic / Logistic scikit-learn: TSNE MNIST Dataset scikit-learn: LocalOutlierFactor scikit-learn: Feature Expansions scikit-learn: Plot OMP vs. LARS scikit-learn: Plot Hierarchical scikit-learn: Text Vectorizers scikit-learn: Plot Fast KMeans scikit-learn: Isolation Forest scikit-learn: Plot Lasso Path scikit-learn: SGDOneClassSVM scikit-learn: SGD Regression scikit-learn: Plot Neighbors scikit-learn: MNIST Dataset scikit-learn: Plot Ward scikit-learn: Sparsify scikit-learn: Lasso scikit-learn: Tree scikit-learn: SAGA scikit-learn: GLM mlpack: scikit_linearridgeregression mlpack: scikit_svm mlpack: scikit_qda mlpack: scikit_ica onednn: Deconvolution Batch shapes_1d - CPU scikit-learn: Glmnet c6i.4xlarge Intel Xeon Platinum 8375C - EFI VGA - Amazon EC2 50.247 1557.47 2967.62 4.39062 2.94925 2.01102 3.97166 852.988 90.358 258.399 18.073 225.038 54.544 62.005 95.314 2252.410 90.721 483.167 153.210 104.031 77.414 1885.951 318.777 75.25 222.478 48.873 259.189 70.936 199.025 349.905 262.867 297.026 125.254 204.786 85.560 74.633 106.328 405.473 50.380 1191.571 268.268 2.23 13.58 30.20 46.04 7.73889 49.300 OpenBenchmarking.org
Scikit-Learn Benchmark: 20 Newsgroups / Logistic Regression OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: 20 Newsgroups / Logistic Regression c6i.4xlarge Intel Xeon Platinum 8375C - EFI VGA - Amazon EC2 11 22 33 44 55 SE +/- 0.06, N = 3 SE +/- 0.21, N = 3 50.25 49.30 1. (F9X) gfortran options: -O0
oneDNN Harness: Recurrent Neural Network Inference - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: Recurrent Neural Network Inference - Engine: CPU c6i.4xlarge 300 600 900 1200 1500 SE +/- 0.86, N = 3 1557.47 MIN: 1539.33 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: Recurrent Neural Network Training - Engine: CPU c6i.4xlarge 600 1200 1800 2400 3000 SE +/- 4.69, N = 3 2967.62 MIN: 2944.31 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: Deconvolution Batch shapes_3d - Engine: CPU c6i.4xlarge 0.9879 1.9758 2.9637 3.9516 4.9395 SE +/- 0.00353, N = 3 4.39062 MIN: 4.36 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 3D - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: IP Shapes 3D - Engine: CPU c6i.4xlarge 0.6636 1.3272 1.9908 2.6544 3.318 SE +/- 0.00799, N = 3 2.94925 MIN: 2.78 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 1D - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: IP Shapes 1D - Engine: CPU c6i.4xlarge 0.4525 0.905 1.3575 1.81 2.2625 SE +/- 0.01758, N = 3 2.01102 MIN: 1.92 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: Convolution Batch Shapes Auto - Engine: CPU c6i.4xlarge 0.8936 1.7872 2.6808 3.5744 4.468 SE +/- 0.01442, N = 3 3.97166 MIN: 3.74 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
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 c6i.4xlarge 200 400 600 800 1000 SE +/- 5.20, N = 3 852.99 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 c6i.4xlarge 20 40 60 80 100 SE +/- 0.63, N = 3 90.36 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 c6i.4xlarge 60 120 180 240 300 SE +/- 0.31, N = 3 258.40 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 c6i.4xlarge 4 8 12 16 20 SE +/- 0.06, N = 3 18.07 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 c6i.4xlarge 50 100 150 200 250 SE +/- 2.40, N = 3 225.04 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 c6i.4xlarge 12 24 36 48 60 SE +/- 0.14, N = 3 54.54 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 c6i.4xlarge 14 28 42 56 70 SE +/- 0.06, N = 3 62.01 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 c6i.4xlarge 20 40 60 80 100 SE +/- 0.74, N = 3 95.31 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Isotonic / Perturbed Logarithm OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Isotonic / Perturbed Logarithm c6i.4xlarge 500 1000 1500 2000 2500 SE +/- 7.47, N = 3 2252.41 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 c6i.4xlarge 20 40 60 80 100 SE +/- 0.08, N = 3 90.72 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 c6i.4xlarge 100 200 300 400 500 SE +/- 1.75, N = 3 483.17 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 c6i.4xlarge 30 60 90 120 150 SE +/- 0.75, N = 3 153.21 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 c6i.4xlarge 20 40 60 80 100 SE +/- 0.21, N = 3 104.03 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 c6i.4xlarge 20 40 60 80 100 SE +/- 0.32, N = 3 77.41 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Isotonic / Logistic OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Isotonic / Logistic c6i.4xlarge 400 800 1200 1600 2000 SE +/- 8.47, N = 3 1885.95 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 c6i.4xlarge 70 140 210 280 350 SE +/- 0.31, N = 3 318.78 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: LocalOutlierFactor OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: LocalOutlierFactor c6i.4xlarge 20 40 60 80 100 SE +/- 0.14, N = 3 75.25 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Feature Expansions OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Feature Expansions c6i.4xlarge 50 100 150 200 250 SE +/- 0.08, N = 3 222.48 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 c6i.4xlarge 11 22 33 44 55 SE +/- 0.19, N = 3 48.87 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Hierarchical OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Hierarchical c6i.4xlarge 60 120 180 240 300 SE +/- 1.56, N = 3 259.19 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Text Vectorizers OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Text Vectorizers c6i.4xlarge 16 32 48 64 80 SE +/- 0.04, N = 3 70.94 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 c6i.4xlarge 40 80 120 160 200 SE +/- 0.99, N = 3 199.03 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Isolation Forest OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Isolation Forest c6i.4xlarge 80 160 240 320 400 SE +/- 0.82, N = 3 349.91 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 c6i.4xlarge 60 120 180 240 300 SE +/- 0.86, N = 3 262.87 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: SGDOneClassSVM OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SGDOneClassSVM c6i.4xlarge 60 120 180 240 300 SE +/- 0.38, N = 3 297.03 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: SGD Regression OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SGD Regression c6i.4xlarge 30 60 90 120 150 SE +/- 0.45, N = 3 125.25 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Neighbors OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Neighbors c6i.4xlarge 40 80 120 160 200 SE +/- 0.88, N = 3 204.79 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: MNIST Dataset OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: MNIST Dataset c6i.4xlarge 20 40 60 80 100 SE +/- 0.07, N = 3 85.56 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Plot Ward OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Ward c6i.4xlarge 20 40 60 80 100 SE +/- 0.02, N = 3 74.63 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Sparsify OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Sparsify c6i.4xlarge 20 40 60 80 100 SE +/- 0.07, N = 3 106.33 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Lasso OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Lasso c6i.4xlarge 90 180 270 360 450 SE +/- 3.54, N = 3 405.47 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: Tree OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Tree c6i.4xlarge 11 22 33 44 55 SE +/- 0.20, N = 3 50.38 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: SAGA OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SAGA c6i.4xlarge 300 600 900 1200 1500 SE +/- 1.80, N = 3 1191.57 1. (F9X) gfortran options: -O0
Scikit-Learn Benchmark: GLM OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: GLM c6i.4xlarge 60 120 180 240 300 SE +/- 0.45, N = 3 268.27 1. (F9X) gfortran options: -O0
Mlpack Benchmark Benchmark: scikit_linearridgeregression OpenBenchmarking.org Seconds, Fewer Is Better Mlpack Benchmark Benchmark: scikit_linearridgeregression c6i.4xlarge 0.5018 1.0036 1.5054 2.0072 2.509 SE +/- 0.01, N = 3 2.23
Mlpack Benchmark Benchmark: scikit_svm OpenBenchmarking.org Seconds, Fewer Is Better Mlpack Benchmark Benchmark: scikit_svm c6i.4xlarge 3 6 9 12 15 SE +/- 0.17, N = 3 13.58
Mlpack Benchmark Benchmark: scikit_qda OpenBenchmarking.org Seconds, Fewer Is Better Mlpack Benchmark Benchmark: scikit_qda c6i.4xlarge 7 14 21 28 35 SE +/- 0.01, N = 3 30.20
Mlpack Benchmark Benchmark: scikit_ica OpenBenchmarking.org Seconds, Fewer Is Better Mlpack Benchmark Benchmark: scikit_ica c6i.4xlarge 10 20 30 40 50 SE +/- 0.11, N = 3 46.04
oneDNN Harness: Deconvolution Batch shapes_1d - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.4 Harness: Deconvolution Batch shapes_1d - Engine: CPU c6i.4xlarge 2 4 6 8 10 SE +/- 0.14831, N = 15 7.73889 MIN: 5.3 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
Phoronix Test Suite v10.8.4