Jaros, M;
Sasak, T;
Treeby, BE;
Jaros, J;
(2021)
Estimation of Execution Parameters for k-Wave Simulations.
In: Kozubek, T and Arbenz, P and Jaros, J and Ríha, L and Sístek, J and Tichý, P, (eds.)
High Performance Computing in Science and Engineering. HPCSE 2019.
(pp. pp. 116-134).
Springer: Cham, Switzerland.
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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.
| Type: | Proceedings paper |
|---|---|
| Title: | Estimation of Execution Parameters for k-Wave Simulations |
| ISBN-13: | 978-3-030-67076-4 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-67077-1_7 |
| Publisher version: | https://doi.org/10.1007/978-3-030-67077-1 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Workflow management system, Performance data collection, Interpolation, Job scheduling, HPC as a service |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10120219 |
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