Scikit-Learn

Scikit-learn is a Python module for machine learning built on NumPy, SciPy, and is BSD-licensed.

To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark scikit-learn.

Project Site

scikit-learn.org

Source Repository

github.com

Test Created

28 September 2016

Last Updated

10 May 2023

Test Maintainer

Michael Larabel

Test Type

System

Average Install Time

1 Minute, 50 Seconds

Average Run Time

2 Minutes, 6 Seconds

Test Dependencies

Python + C/C++ Compiler Toolchain + CMake + Fortran + Meson Build System

Accolades

100k+ Downloads

Supported Platforms

* Uploading of benchmark result data to OpenBenchmarking.org is always optional (opt-in) via the Phoronix Test Suite for users wishing to share their results publicly.
** Data based on those opting to upload their test results to OpenBenchmarking.org and users enabling the opt-in anonymous statistics reporting while running benchmarks from an Internet-connected platform.
*** Test profile page view reporting began March 2021.
Data updated weekly as of 15 May 2024.

Revision History

pts/scikit-learn-2.0.0 [View Source] Wed, 10 May 2023 09:00:04 GMT
Update against SciKit-Learn 1.2.2 upstream, enable more tests.

pts/scikit-learn-1.2.0 [View Source] Sun, 20 Nov 2022 14:33:40 GMT
Update test against upstream, add more benchmark options...

pts/scikit-learn-1.1.0 [View Source] Fri, 10 Jan 2020 09:06:48 GMT
Update test profile per https://github.com/phoronix-test-suite/test-profiles/pull/124 but bump version to 1.1.0 due to scikit-learn version change. Also explicitly use python3 binary name.

pts/scikit-learn-1.0.1 [View Source] Thu, 04 May 2017 10:41:34 GMT
Use unzip -o

pts/scikit-learn-1.0.0 [View Source] Wed, 28 Sep 2016 09:45:52 GMT
Initial commit.

Suites Using This Test

Machine Learning

HPC - High Performance Computing

CPU Massive

Server CPU Tests

Python

Performance Metrics

Analyze Test Configuration:

Scikit-Learn 0.17.1

OpenBenchmarking.org metrics for this test profile configuration based on 1,059 public results since 1 August 2017 with the latest data as of 5 June 2021.

Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.

Component

Percentile Rank

# Compatible Public Results

Seconds (Average)

Intel Core i7-7700K

94th

9 ^{+/- 1}

2 x AMD EPYC 7742 64-Core

90th

AMD Ryzen 9 3900X 12-Core

86th

Intel Core i9-7900X

86th

Intel Core i5-6500

85th

11 ^{+/- 2}

Mid-Tier

75th

> 13

Intel Xeon E3-1235L v5

71st

14 ^{+/- 2}

Intel Core i7-4770K

69th

14 ^{+/- 1}

Intel Core i7-8750H

68th

14 ^{+/- 1}

Intel Core i7-4960X

62nd

16 ^{+/- 1}

Intel Core i5-6260U

58th

19 ^{+/- 1}

Intel Xeon E5-2609 v4

55th

22 ^{+/- 3}

Intel Pentium G4400

54th

22 ^{+/- 1}

Median

50th

AMD Ryzen 5 1600X Six-Core

45th

27 ^{+/- 1}

Intel Core i7-3960X

43rd

29 ^{+/- 1}

ARMv8 Cortex-A72 16-Core

41st

31 ^{+/- 1}

AMD Athlon II X4 620

34th

67 ^{+/- 7}

Low-Tier

25th

> 150

Intel Core i3-7100

25th

151

POWER9 altivec supported 144-Core

11th

227

POWER9 altivec supported 88-Core

11th

229 ^{+/- 1}

POWER9 altivec supported 32-Core

10th

231

Intel Core i3-5005U

10th

247 ^{+/- 6}

POWER9 altivec supported 64-Core

9th

259 ^{+/- 1}

Intel Xeon Gold 6138

7th

299 ^{+/- 9}

ARMv7 rev 4 4-Core

4th

814 ^{+/- 34}

AArch64 rev 4

3rd

903 ^{+/- 87}

ARMv8 Cortex-A53 4-Core

2nd

977 ^{+/- 136}

ARMv7 rev 5 4-Core

1st

2182 ^{+/- 206}

Based on OpenBenchmarking.org data, the selected test / test configuration (Scikit-Learn 0.17.1) has an average run-time of 6 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.5%.

Tested CPU Architectures

This benchmark has been successfully tested on the below mentioned architectures. The CPU architectures listed is where successful OpenBenchmarking.org result uploads occurred, namely for helping to determine if a given test is compatible with various alternative CPU architectures.

CPU Architecture

Kernel Identifier

Verified On

Intel / AMD x86 64-bit

x86_64

(Many Processors)

IBM POWER (PowerPC) 64-bit

ppc64le

POWER8, POWER9 16-Core, POWER9 4-Core, POWER9 44-Core, POWER9 80-Core, POWER9 altivec supported 144-Core, POWER9 altivec supported 32-Core, POWER9 altivec supported 44-Core, POWER9 altivec supported 64-Core, POWER9 altivec supported 88-Core, POWER9 altivec supported 96-Core

MIPS

mips

Baikal-T1 1.2 GHz MIPS P5600 V3.0 FPU V2.0

Intel / AMD x86 32-bit

i686

(Many Processors)

ARMv7 32-bit

armv7l

ARMv7 Cortex-A72 4-Core, ARMv7 rev 1 4-Core, ARMv7 rev 3 4-Core, ARMv7 rev 3 8-Core, ARMv7 rev 4 4-Core, ARMv7 rev 5 4-Core, ARMv7 rev 5 8-Core

ARMv8 64-bit

aarch64

AArch64 rev 4, ARMVv8 Cortex-A53 4-Core, ARMVv8 Cortex-A73 6-Core, ARMv8 Cortex-A53 24-Core, ARMv8 Cortex-A53 4-Core, ARMv8 Cortex-A72 16-Core, ARMv8 Cortex-A72 6-Core, ARMv8 Cortex-A72 8-Core, ARMv8 Cortex-A73, ARMv8 rev 0 8-Core, ARMv8 rev 1 4-Core, ARMv8 rev 3 4-Core, ARMv8 rev 3 6-Core, ARMv8 rev 4 8-Core, Amlogic, Ampere eMAG ARMv8 32-Core, Cavium ThunderX, Rockchip, Rockchip ARMv8 Cortex-A53 4-Core