Publication detail

Estimation of Execution Parameters for k-Wave Simulations

JAROŠ, M. SASÁK, T. TREEBY, B. JAROŠ, J.

Original Title

Estimation of Execution Parameters for k-Wave Simulations

Type

conference paper

Language

English

Original Abstract

Estimation of execution parameters takes centre stage in automatic offloading of complex biomedical workflows to cloud and high performance facilities. Since ordinary users have no or very limited knowledge of the performance characteristics of particular tasks in the workflow, the scheduling system has to have the capabilities to select appropriate amount of compute resources, e.g., compute nodes, GPUs, or processor cores and estimate the execution time and cost. The presented approach considers a fixed set of executables that can be used to create custom workflows, and collects performance data of successfully computed tasks. Since the workflows may differ in the structure and size of the input data, the execution parameters can only be obtained by searching the performance database and interpolating between similar tasks. This paper shows it is possible to predict the execution time and cost with a high confidence. If the task parameters are found in the performance database, the mean interpolation error stays below 2.29%. If only similar tasks are found, the mean interpolation error may grow up to 15%. Nevertheless, this is still an acceptable error since the cluster performance may vary on order of percent as well.

Keywords

Workflow management system, Performance data collection, Interpolation, Job scheduling, HPC as a service 

Authors

JAROŠ, M.; SASÁK, T.; TREEBY, B.; JAROŠ, J.

Released

8. 1. 2021

Publisher

Springer Nature Switzerland AG

Location

Cham

ISBN

978-3-030-67076-4

Book

High Performance Computing in Science and Engineering. HPCSE 2019

Edition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages from

116

Pages to

134

Pages count

19

URL

https://link.springer.com/chapter/10.1007/978-3-030-67077-1_7

BibTex

@inproceedings{BUT168118,
  author="Marta {Jaroš} and Tomáš {Sasák} and Bradley {Treeby} and Jiří {Jaroš}",
  title="Estimation of Execution Parameters for k-Wave Simulations",
  booktitle="High Performance Computing in Science and Engineering. HPCSE 2019",
  year="2021",
  series="Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  pages="116--134",
  publisher="Springer Nature Switzerland AG",
  address="Cham",
  doi="10.1007/978-3-030-67077-1\{_}7",
  isbn="978-3-030-67076-4",
  url="https://link.springer.com/chapter/10.1007/978-3-030-67077-1_7"
}

Documents

HPCSE_Jaros_2021.pdf