Mlpack Benchmark

Mlpack benchmark scripts for machine learning libraries

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

Project Site

github.com

Test Created

10 January 2020

Last Updated

27 September 2020

Test Maintainer

Yu Ma 

Test Type

System

Average Install Time

18 Seconds

Average Run Time

1 Minute, 39 Seconds

Test Dependencies

Python Scipy + Python Sklearn + Python + C/C++ Compiler Toolchain

Accolades

10k+ Downloads

Supported Platforms


Public Result UploadsReported Installs*Test Completions*OpenBenchmarking.orgEventsMlpack Benchmark Popularity Statisticspts/mlpack2020.012020.022020.032020.042020.052020.062020.072020.082020.092020.102020.112020.122021.012021.022021.032021.046001200180024003000
* 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.
Data current as of Sat, 10 Apr 2021 08:59:46 GMT.
scikit_svm30.6%scikit_qda23.7%scikit_linearridgeregression23.3%scikit_ica22.4%Benchmark Option PopularityOpenBenchmarking.org

Revision History

pts/mlpack-1.0.2   [View Source]   Sun, 27 Sep 2020 08:59:52 GMT
Set --user for pip3 argument to fix install on some distros.

pts/mlpack-1.0.1   [View Source]   Mon, 24 Feb 2020 07:53:06 GMT
Add new tests per https://github.com/phoronix-test-suite/test-profiles/pull/129

pts/mlpack-1.0.0   [View Source]   Fri, 10 Jan 2020 09:28:52 GMT
Initial commit of mlpack per https://github.com/phoronix-test-suite/test-profiles/pull/124

Suites Using This Test

Machine Learning

HPC - High Performance Computing

Python


Performance Metrics

Analyze Test Configuration:

Mlpack Benchmark

Benchmark: scikit_svm

OpenBenchmarking.org metrics for this test profile configuration based on 1,215 public results since 10 January 2020 with the latest data as of 30 March 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
# Matching Public Results
Seconds (Average)
96th
4
11.6 +/- 0.1
83rd
3
15.3 +/- 0.2
80th
3
15.8 +/- 0.2
79th
3
16.0 +/- 0.1
78th
4
16.1 +/- 0.5
Mid-Tier
75th
> 16.3
75th
20
16.3 +/- 0.1
74th
17
16.6 +/- 0.3
72nd
8
16.9 +/- 0.4
71st
9
17.1 +/- 0.4
69th
3
17.5 +/- 0.5
66th
3
18.1 +/- 0.5
62nd
7
18.9 +/- 0.7
59th
11
19.4 +/- 0.2
58th
3
19.7 +/- 0.2
55th
19
20.7 +/- 0.3
Median
50th
21.7
50th
4
22.1 +/- 0.2
49th
7
22.3 +/- 0.5
47th
12
22.5 +/- 0.1
47th
4
22.7 +/- 0.1
44th
4
23.6 +/- 0.1
37th
8
25.4 +/- 0.2
36th
9
25.5 +/- 3.7
29th
5
26.9 +/- 0.1
Low-Tier
25th
> 27.3
23rd
6
27.8 +/- 0.3
22nd
3
28.0 +/- 0.2
18th
4
28.8 +/- 0.2
7th
4
29.5 +/- 0.1
6th
10
30.2 +/- 3.7
3rd
4
33.3 +/- 0.2
OpenBenchmarking.orgDistribution Of Public Results - Benchmark: scikit_svm1214 Results Range From 1 To 103 Seconds110192837465564738291100109110220330440550

Based on OpenBenchmarking.org data, the selected test / test configuration (Mlpack Benchmark - Benchmark: scikit_svm) has an average run-time of 2 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.

OpenBenchmarking.orgMinutesTime Required To Complete BenchmarkBenchmark: scikit_svmRun-Time246810Min: 1 / Avg: 1.45 / Max: 5

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.6%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsBenchmark: scikit_svmDeviation3691215Min: 0 / Avg: 0.58 / Max: 11

Does It Scale Well With Increasing Cores?

No, based on the automated analysis of the collected public benchmark data, this test / test settings does not generally scale well with increasing CPU core counts. Data based on publicly available results for this test / test settings, separated by vendor, result divided by the reference CPU clock speed, grouped by matching physical CPU core count, and normalized against the smallest core count tested from each vendor for each CPU having a sufficient number of test samples and statistically significant data.

IntelAMDOpenBenchmarking.orgRelative Core Scaling To BaseMlpack Benchmark CPU Core ScalingBenchmark: scikit_svm24681216320.44790.89581.34371.79162.2395

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