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18 April 2024 |
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DALiuGE: A Graph Execution Framework for Harnessing the Astronomical Data Deluge | | Chen Wu
; Rodrigo Tobar
; Kevin Vinsen
; Andreas Wicenec
; Dave Pallot
; Baoqiang Lao
; Ruonan Wang
; Tao An
; Mark Boulton
; Ian Cooper
; Richard Dodson
; Markus Dolensky
; Ying Mei
; Feng Wang
; | | Date: |
24 Feb 2017 | | Abstract: | The Data Activated Liu Graph Engine - DALiuGE - is an execution framework for
processing large astronomical datasets at a scale required by the Square
Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex
data reduction pipelines consisting of both data sets and algorithmic
components and an implementation run-time to execute such pipelines on
distributed resources. By mapping the logical view of a pipeline to its
physical realisation, DALiuGE separates the concerns of multiple stakeholders,
allowing them to collectively optimise large-scale data processing solutions in
a coherent manner. The execution in DALiuGE is data-activated, where each
individual data item autonomously triggers the processing on itself. Such
decentralisation also makes the execution framework very scalable and flexible,
supporting pipeline sizes ranging from less than ten tasks running on a laptop
to tens of millions of concurrent tasks on the second fastest supercomputer in
the world. DALiuGE has been used in production for reducing interferometry data
sets from the Karl E. Jansky Very Large Array and the Mingantu Ultrawide
Spectral Radioheliograph; and is being developed as the execution framework
prototype for the Science Data Processor (SDP) consortium of the Square
Kilometre Array (SKA) telescope. This paper presents a technical overview of
DALiuGE and discusses case studies from the CHILES and MUSER projects that use
DALiuGE to execute production pipelines. In a companion paper, we provide
in-depth analysis of DALiuGE’s scalability to very large numbers of tasks on
two supercomputing facilities. | | Source: | arXiv, 1702.7617 | | Services: | Forum | Review | PDF | Favorites | |
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