Monte Carlo Simulations of Ionised Nebulae

Mocassin is the Monte Carlo Simulations of Ionised Nebulae. MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution.

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

Source Repository

github.com

Test Created

18 September 2020

Last Updated

18 June 2023

Test Maintainer

Michael Larabel 

Test Type

Processor

Average Install Time

20 Seconds

Average Run Time

5 Minutes, 10 Seconds

Test Dependencies

Fortran + OpenMPI + C/C++ Compiler Toolchain

Accolades

10k+ Downloads

Supported Platforms


Public Result Uploads *Reported Installs **Reported Test Completions **Test Profile Page Views ***OpenBenchmarking.orgEventsMonte Carlo Simulations of Ionised Nebulae Popularity Statisticspts/mocassin2020.092020.102020.112020.122021.012021.022021.032021.042021.052021.062021.072021.082021.092021.102021.112021.122022.012022.022022.032022.042022.052022.062022.072022.082022.092022.102022.112022.122023.012023.022023.032023.042023.052023.062023.072023.082023.092023.102023.112023.122024.012024.029001800270036004500
* 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 20 February 2024.
Gas HII4048.7%Dust 2D tau100.051.3%Input Option PopularityOpenBenchmarking.org

Revision History

pts/mocassin-1.1.0   [View Source]   Sun, 18 Jun 2023 10:59:22 GMT
Update against latest upstream.

pts/mocassin-1.0.0   [View Source]   Fri, 18 Sep 2020 17:47:28 GMT
Initial commit of Mocassin - Monte Carlo Simulations of Ionised Nebulae

Suites Using This Test

HPC - High Performance Computing

Scientific Computing

MPI Benchmarks


Performance Metrics

Analyze Test Configuration:

Monte Carlo Simulations of Ionised Nebulae 2.02.73.3

Input: Dust 2D tau100.0

OpenBenchmarking.org metrics for this test profile configuration based on 140 public results since 18 June 2023 with the latest data as of 10 December 2023.

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)
Mid-Tier
75th
> 95
59th
4
119 +/- 2
Median
50th
142
28th
4
199 +/- 5
Low-Tier
25th
> 203
18th
6
216 +/- 8
3rd
4
346 +/- 2
OpenBenchmarking.orgDistribution Of Public Results - Input: Dust 2D tau100.0140 Results Range From 63 To 885 Seconds6392121150179208237266295324353382411440469498527556585614643672701730759788817846875904714212835

Based on OpenBenchmarking.org data, the selected test / test configuration (Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 - Input: Dust 2D tau100.0) has an average run-time of 13 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 BenchmarkInput: Dust 2D tau100.0Run-Time816243240Min: 3 / Avg: 12.11 / Max: 37

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.3%.

OpenBenchmarking.orgPercent, Fewer Is BetterAverage Deviation Between RunsInput: Dust 2D tau100.0Deviation246810Min: 0 / Avg: 0.34 / Max: 4

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)
Loongson LoongArch 64-bit
loongarch64
Loongson-3A6000
ARMv8 64-bit
aarch64
ARMv8 Cortex-A72 4-Core, ARMv8 Neoverse-N1, ARMv8 Neoverse-V1, Apple M2

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