c7g.4xlarge

c7g.4xlarge

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2406285-NE-C7G4XLARG72
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results
Show Result Confidence Charts
Allow Limiting Results To Certain Suite(s)

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Disable Color Branding
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Toggle/Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
c7g.4xlarge
June 25
  10 Hours, 49 Minutes
ARMv8 Neoverse-V1 - - Amazon EC2 c7g.4xlarge (1.0
June 26
  1 Minute
tst11
June 28
  2 Minutes
n
June 28
  2 Minutes
Invert Behavior (Only Show Selected Data)
  2 Hours, 43 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


c7g.4xlargeProcessorMotherboardChipsetMemoryDiskNetworkOSKernelCompilerFile-SystemSystem LayerVulkanc7g.4xlargeARMv8 Neoverse-V1 - - Amazon EC2 c7g.4xlarge (1.0tst11nARMv8 Neoverse-V1 (16 Cores)Amazon EC2 c7g.4xlarge (1.0 BIOS)Amazon Device 020032GB215GB Amazon Elastic Block StoreAmazon ElasticUbuntu 22.046.5.0-1020-aws (aarch64)GCC 11.4.0ext4amazon1.3.255OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madvisePython Details- c7g.4xlarge: Python 3.7.16- ARMv8 Neoverse-V1 - - Amazon EC2 c7g.4xlarge (1.0: Python 3.11.9Security Details- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Mitigation of CSV2 BHB + srbds: Not affected + tsx_async_abort: Not affected Compiler Details- ARMv8 Neoverse-V1 - - Amazon EC2 c7g.4xlarge (1.0, tst11, n: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --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-link-serialization=2 --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-target-system-zlib=auto -v

c7g.4xlargellama-cpp: Meta-Llama-3-8B-Instruct-Q8_0.ggufmlpack: scikit_icamlpack: scikit_qdamlpack: scikit_svmmlpack: scikit_linearridgeregressionscikit-learn: GLMscikit-learn: Treescikit-learn: Lassoscikit-learn: Sparsifyscikit-learn: Plot Wardscikit-learn: Plot Neighborsscikit-learn: SGD Regressionscikit-learn: SGDOneClassSVMscikit-learn: Plot Fast KMeansscikit-learn: Plot Hierarchicalscikit-learn: Feature Expansionsscikit-learn: Isotonic / Logisticscikit-learn: Plot Incremental PCAscikit-learn: Hist Gradient Boostingscikit-learn: Sample Without Replacementscikit-learn: Covertype Dataset Benchmarkscikit-learn: Isotonic / Perturbed Logarithmscikit-learn: Hist Gradient Boosting Threadingscikit-learn: Plot Singular Value Decompositionscikit-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 Iterationsc7g.4xlargeARMv8 Neoverse-V1 - - Amazon EC2 c7g.4xlarge (1.0tst11n17.2136.5530.6817.042.44301.73974.621272.994103.31871.145214.07583.124386.466107.137234.705138.6031363.83628.194247.538214.181438.5221786.126104.78462.6758.677168.03843.080202.00163.819670.29621.5921.87OpenBenchmarking.org

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'tensorflow'

Llama.cpp

OpenBenchmarking.orgTokens Per Second, More Is BetterLlama.cpp b3067Model: Meta-Llama-3-8B-Instruct-Q8_0.ggufc7g.4xlargentst11510152025SE +/- 0.10, N = 3SE +/- 0.03, N = 3SE +/- 0.14, N = 317.2121.8721.591. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -mcpu=native -lopenblas

Mlpack Benchmark

Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_icac7g.4xlarge816243240SE +/- 0.03, N = 336.55

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_qdac7g.4xlarge714212835SE +/- 0.06, N = 330.68

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_svmc7g.4xlarge48121620SE +/- 0.02, N = 317.04

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_linearridgeregressionc7g.4xlarge0.5491.0981.6472.1962.745SE +/- 0.00, N = 32.44

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: GLMc7g.4xlarge70140210280350SE +/- 0.46, N = 3301.741. (F9X) gfortran options: -O0

Benchmark: SAGA

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Treec7g.4xlarge20406080100SE +/- 0.62, N = 374.621. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Lassoc7g.4xlarge60120180240300SE +/- 1.58, N = 3272.991. (F9X) gfortran options: -O0

Benchmark: Glmnet

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'glmnet'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparsifyc7g.4xlarge20406080100SE +/- 0.01, N = 3103.321. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Wardc7g.4xlarge1632486480SE +/- 0.09, N = 371.151. (F9X) gfortran options: -O0

Benchmark: MNIST Dataset

c7g.4xlarge: The test quit with a non-zero exit status. E: ImportError: Returning pandas objects requires pandas to be installed. Alternatively, explicitly set `as_frame=False` and `parser='liac-arff'`.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Neighborsc7g.4xlarge50100150200250SE +/- 0.94, N = 3214.081. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGD Regressionc7g.4xlarge20406080100SE +/- 0.18, N = 383.121. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: SGDOneClassSVMc7g.4xlarge80160240320400SE +/- 2.12, N = 3386.471. (F9X) gfortran options: -O0

Benchmark: Plot Lasso Path

c7g.4xlarge: The test quit with a non-zero exit status. E: sklearn.utils._param_validation.InvalidParameterError: The 'effective_rank' parameter of make_regression must be an int in the range [1, inf) or None. Got 1.5 instead.

Benchmark: Isolation Forest

c7g.4xlarge: The test quit with a non-zero exit status. E: ImportError: Using `parser='pandas'` wit dense data requires pandas to be installed. Alternatively, explicitly set `parser='liac-arff'`.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Fast KMeansc7g.4xlarge20406080100SE +/- 0.17, N = 3107.141. (F9X) gfortran options: -O0

Benchmark: Text Vectorizers

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Hierarchicalc7g.4xlarge50100150200250SE +/- 0.15, N = 3234.711. (F9X) gfortran options: -O0

Benchmark: Plot OMP vs. LARS

c7g.4xlarge: The test quit with a non-zero exit status. E: TypeError: got an unexpected keyword argument 'data_transposed'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Feature Expansionsc7g.4xlarge306090120150SE +/- 0.14, N = 3138.601. (F9X) gfortran options: -O0

Benchmark: LocalOutlierFactor

c7g.4xlarge: The test quit with a non-zero exit status. E: ImportError: Using `parser='pandas'` wit dense data requires pandas to be installed. Alternatively, explicitly set `parser='liac-arff'`.

Benchmark: TSNE MNIST Dataset

c7g.4xlarge: The test quit with a non-zero exit status. E: ImportError: Returning pandas objects requires pandas to be installed. Alternatively, explicitly set `as_frame=False` and `parser='liac-arff'`.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isotonic / Logisticc7g.4xlarge30060090012001500SE +/- 0.34, N = 31363.841. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Incremental PCAc7g.4xlarge714212835SE +/- 0.23, N = 328.191. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boostingc7g.4xlarge50100150200250SE +/- 8.01, N = 9247.541. (F9X) gfortran options: -O0

Benchmark: Plot Parallel Pairwise

c7g.4xlarge: 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

c7g.4xlarge: The test quit with a non-zero exit status.

Benchmark: RCV1 Logreg Convergencet

c7g.4xlarge: 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 Replacementc7g.4xlarge50100150200250SE +/- 0.28, N = 3214.181. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Covertype Dataset Benchmarkc7g.4xlarge100200300400500SE +/- 2.42, N = 3438.521. (F9X) gfortran options: -O0

Benchmark: Hist Gradient Boosting Adult

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Isotonic / Perturbed Logarithmc7g.4xlarge400800120016002000SE +/- 0.39, N = 31786.131. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Threadingc7g.4xlarge20406080100SE +/- 0.59, N = 3104.781. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Singular Value Decompositionc7g.4xlarge1428425670SE +/- 0.39, N = 362.681. (F9X) gfortran options: -O0

Benchmark: Hist Gradient Boosting Higgs Boson

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: 20 Newsgroups / Logistic Regressionc7g.4xlarge246810SE +/- 0.023, N = 38.6771. (F9X) gfortran options: -O0

Benchmark: 20 Newsgroups / Logistic Regression

ARMv8 Neoverse-V1 - - Amazon EC2 c7g.4xlarge (1.0: The test quit with a non-zero exit status. E: ImportError: /lib/aarch64-linux-gnu/liblapack.so.3: undefined symbol: gotoblas

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Plot Polynomial Kernel Approximationc7g.4xlarge4080120160200SE +/- 0.70, N = 3168.041. (F9X) gfortran options: -O0

Benchmark: Plot Non-Negative Matrix Factorization

c7g.4xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Hist Gradient Boosting Categorical Onlyc7g.4xlarge1020304050SE +/- 0.82, N = 1343.081. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Kernel PCA Solvers / Time vs. N Samplesc7g.4xlarge4080120160200SE +/- 2.57, N = 3202.001. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Kernel PCA Solvers / Time vs. N Componentsc7g.4xlarge1428425670SE +/- 0.47, N = 1563.821. (F9X) gfortran options: -O0

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 1.2.2Benchmark: Sparse Random Projections / 100 Iterationsc7g.4xlarge140280420560700SE +/- 0.72, N = 3670.301. (F9X) gfortran options: -O0