Reproducible and hackable software benchmarking with(out) compute clusters

Abstract We present Simsala, an easy-to-install and easy-to-use collection of scripts supporting benchmarking on clusters of compute nodes. While designed with applications for benchmarking solving technologies like SAT and extensions, our solution can be easily transferred to many other application scenarios as well. In this work, we discuss the design objectives behind Simsala, provide some implementation details, and illustrate with case studies how Simsala has been applied in the past for extensive evaluations.

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Publication Details

Journal
International Journal on Software Tools for Technology Transfer
Published
2025-05-19
DOI
https://doi.org/10.1007/s10009-025-00811-3
Citations
1
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
4.17
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article

Reproducible and hackable software benchmarking with(out) compute clusters

Maximilian Heisinger, Martina Seidl
1 citations
International Journal on Software Tools for Technology Transfer
Scientific Computing and Data Management
4.17
article

Reproducible and hackable software benchmarking with(out) compute clusters

Maximilian Heisinger, Martina Seidl
article en
1 citations

Abstract

Abstract We present Simsala, an easy-to-install and easy-to-use collection of scripts supporting benchmarking on clusters of compute nodes. While designed with applications for benchmarking solving technologies like SAT and extensions, our solution can be easily transferred to many other application scenarios as well. In this work, we discuss the design objectives behind Simsala, provide some implementation details, and illustrate with case studies how Simsala has been applied in the past for extensive evaluations.

International Journal on Software Tools for Technology TransferVol. 27(4)
Johannes Kepler University of Linz (AT)
Openalex Percentile: Top 6%
Scientific Computing and Data Management
4.17
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