Show simple item record

dc.contributor.authorMechev, A.
dc.contributor.authorPlaat, A.
dc.contributor.authorOonk, J.
dc.contributor.authorIntema, Hubertus
dc.contributor.authorRöttgering, H.
dc.identifier.citationMechev, A. and Plaat, A. and Oonk, J. and Intema, H. and Röttgering, H. 2018. Pipeline Collector: Gathering performance data for distributed astronomical pipelines. Astronomy and Computing. 24: pp. 117-128.

Modern astronomical data processing requires complex software pipelines to process ever growing datasets. For radio astronomy, these pipelines have become so large that they need to be distributed across a computational cluster. This makes it difficult to monitor the performance of each pipeline step. To gain insight into the performance of each step, a performance monitoring utility needs to be integrated with the pipeline execution. In this work we have developed such a utility and integrated it with the calibration pipeline of the Low Frequency Array, LOFAR, a leading radio telescope. We tested the tool by running the pipeline on several different compute platforms and collected the performance data. Based on this data, we make well informed recommendations on future hardware and software upgrades. The aim of these upgrades is to accelerate the slowest processing steps for this LOFAR pipeline. The pipeline_collector suite is open source and will be incorporated in future LOFAR pipelines to create a performance database for all LOFAR processing.

dc.titlePipeline Collector: Gathering performance data for distributed astronomical pipelines
dc.typeJournal Article
dcterms.source.titleAstronomy and Computing

© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license

curtin.accessStatusOpen access

Files in this item


This item appears in the following Collection(s)

Show simple item record