arXiv subjects

Andreas Wicenec

Publications and source records attributed to Andreas Wicenec.

31 records · Page 2Linked to original sources

arXiv2018

CHILES: HI morphology and galaxy environment at z=0.12 and z=0.17

We present a study of 16 HI-detected galaxies found in 178 hours of observations from Epoch 1 of the COSMOS HI Large Extragalactic Survey (CHILES). We focus on two redshift ranges between 0.108 <= z <= 0.127 and 0.162 <= z <= 0.183 which are among the worst affected by radio frequency interference (RFI). While this represents only 10% of the total frequency coverage and 18% of the total expected time on source compared to what will be the full CHILES survey, we demonstrate that our data reduction pipeline recovers high quality data even in regions severely impacted by RFI. We report on our in-depth testing of an automated spectral line source finder to produce HI total intensity maps which we present side-by-side with significance maps to evaluate the reliability of the morphology recovered by the source finder. We recommend that this become a common place manner of presenting data from upcoming HI surveys of resolved objects. We use the COSMOS 20k group catalogue, and we extract filamentary structure using the topological DisPerSE algorithm to evaluate the \hi\ morphology in the context of both local and large-scale environments and we discuss the shortcomings of both methods. Many of the detections show disturbed HI morphologies suggesting they have undergone a recent interaction which is not evident from deep optical imaging alone. Overall, the sample showcases the broad range of ways in which galaxies interact with their environment. This is a first look at the population of galaxies and their local and large-scale environments observed in HI by CHILES at redshifts beyond the z=0.1 Universe.

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arXiv2018

Partitioning SKA Dataflows for Optimal Graph Execution

Optimizing data-intensive workflow execution is essential to many modern scientific projects such as the Square Kilometre Array (SKA), which will be the largest radio telescope in the world, collecting terabytes of data per second for the next few decades. At the core of the SKA Science Data Processor is the graph execution engine, scheduling tens of thousands of algorithmic components to ingest and transform millions of parallel data chunks in order to solve a series of large-scale inverse problems within the power budget. To tackle this challenge, we have developed the Data Activated Liu Graph Engine (DALiuGE) to manage data processing pipelines for several SKA pathfinder projects. In this paper, we discuss the DALiuGE graph scheduling sub-system. By extending previous studies on graph scheduling and partitioning, we lay the foundation on which we can develop polynomial time optimization methods that minimize both workflow execution time and resource footprint while satisfying resource constraints imposed by individual algorithms. We show preliminary results obtained from three radio astronomy data pipelines.

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arXiv2017

AdiosStMan: Parallelizing Casacore Table Data System Using Adaptive IO System

In this paper, we investigate the Casacore Table Data System (CTDS) used in the casacore and CASA libraries, and methods to parallelize it. CTDS provides a storage manager plugin mechanism for third-party devel- opers to design and implement their own CTDS storage managers. Hav- ing this in mind, we looked into various storage backend techniques that can possibly enable parallel I/O for CTDS by implementing new storage managers. After carrying on benchmarks showing the excellent parallel I/O throughput of the Adaptive IO System (ADIOS), we implemented an ADIOS based parallel CTDS storage manager. We then applied the CASA MSTransform frequency split task to verify the ADIOS Storage Manager. We also ran a series of performance tests to examine the I/O throughput in a massively parallel scenario.

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arXiv2017

DALiuGE: A Graph Execution Framework for Harnessing the Astronomical Data Deluge

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.

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arXiv2016

IVOA Recommendation: VOTable Format Definition Version 1.3

This document describes the structures making up the VOTable standard. The main part of this document describes the adopted part of the VOTable standard; it is followed by appendices presenting extensions which have been proposed and/or discussed, but which are not part of the standard.

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arXiv2016

Highest Redshift Image of Neutral Hydrogen in Emission: A CHILES Detection of a Starbursting Galaxy at z=0.376

Our current understanding of galaxy evolution still has many uncertainties associated with the details of accretion, processing, and removal of gas across cosmic time. The next generation of radio telescopes will image the neutral hydrogen (HI) in galaxies over large volumes at high redshifts, which will provide key insights into these processes. We are conducting the COSMOS HI Large Extragalactic Survey (CHILES) with the Karl G. Jansky Very Large Array, which is the first survey to simultaneously observe HI from z=0 to z~0.5. Here, we report the highest redshift HI 21-cm detection in emission to date of the luminous infrared galaxy (LIRG) COSMOS J100054.83+023126.2 at z=0.376 with the first 178 hours of CHILES data. The total HI mass is $(2.9\pm1.0)\times10^{10}~M_\odot$, and the spatial distribution is asymmetric and extends beyond the galaxy. While optically the galaxy looks undisturbed, the HI distribution suggests an interaction with candidate a candidate companion. In addition, we present follow-up Large Millimeter Telescope CO observations that show it is rich in molecular hydrogen, with a range of possible masses of $(1.8-9.9)\times10^{10}~M_\odot$. This is the first study of the HI and CO in emission for a single galaxy beyond z~0.2.

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arXiv2015

Imaging SKA-Scale data in three different computing environments

We present the results of our investigations into options for the computing platform for the imaging pipeline in the CHILES project, an ultra-deep HI pathfinder for the era of the Square Kilometre Array. CHILES pushes the current computing infrastructure to its limits and understanding how to deliver the images from this project is clarifying the Science Data Processing requirements for the SKA. We have tested three platforms: a moderately sized cluster, a massive High Performance Computing (HPC) system, and the Amazon Web Services (AWS) cloud computing platform. We have used well-established tools for data reduction and performance measurement to investigate the behaviour of these platforms for the complicated access patterns of real-life Radio Astronomy data reduction. All of these platforms have strengths and weaknesses and the system tools allow us to identify and evaluate them in a quantitative manner. With the insights from these tests we are able to complete the imaging pipeline processing on both the HPC platform and also on the cloud computing platform, which paves the way for meeting big data challenges in the era of SKA in the field of Radio Astronomy. We discuss the implications that all similar projects will have to consider, in both performance and costs, to make recommendations for the planning of Radio Astronomy imaging workflows.

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arXiv2015

Delivering SKA Science

The SKA will be capable of producing a stream of science data products that are Exa-scale in terms of their storage and processing requirements. This Google-scale enterprise is attracting considerable international interest and excitement from within the industrial and academic communities. In this chapter we examine the data flow, storage and processing requirements of a number of key SKA survey science projects to be executed on the baseline SKA1 configuration. Based on a set of conservative assumptions about trends for HPC and storage costs, and the data flow process within the SKA Observatory, it is apparent that survey projects of the scale proposed will potentially drive construction and operations costs beyond the current anticipated SKA1 budget. This implies a sharing of the resources and costs to deliver SKA science between the community and what is contained within the SKA Observatory. A similar situation was apparent to the designers of the LHC more than 10 years ago. We propose that it is time for the SKA project and community to consider the effort and process needed to design and implement a distributed SKA science data system that leans on the lessons of other projects and looks to recent developments in Cloud technologies to ensure an affordable, effective and global achievement of SKA science goals.

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arXiv2014

Astronomical Imagery: Considerations For a Contemporary Approach with JPEG2000

The new wide-field radio telescopes, such as: ASKAP, MWA, LOFAR, eVLA and SKA; will produce spectral-imaging data-cubes (SIDC) of unprecedented size -- in the order of hundreds of Petabytes. Servicing such data as images to the end-user in a traditional manner and formats is likely going to encounter significant performance fallbacks. We discuss the requirements for extremely large SIDCs, and in this light we analyse the applicability of the approach taken in the JPEG2000 (ISO/IEC 15444) standards. We argue the case for the adaptation of contemporary industry standards and technologies vs the modification of legacy astronomy standards or the development new from scratch.

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arXiv2013

Optimising NGAS for the MWA Archive

The Murchison Widefield Array (MWA) is a next-generation radio telescope, generating visibility data products continuously at about 400 MB/s. Efficiently managing and archiving this data is a challenge. The MWA Archive consists of dataflows and storage sub-systems distributed across three tiers. At its core is the open source software - the Next-Generation Archive System (NGAS) - that was initially developed in ESO. However, to meet the MWA data challenge, we have tailored and optimised NGAS to achieve high-throughput data ingestion, efficient dataflow management, multi-tiered data storage and processing-aware data staging.

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arXiv2013

Extremely Large Images: Considerations for Contemporary Approach

The new widefield radio telescopes, such as: ASKAP,MWA, LOFAR, eVLA and SKA; will produce spectral-imaging data-cubes (SIDC) of unprecedented volumes in the order of hundreds of Petabytes. Servicing such data as images to the end-user may encounter challenges unforeseen during the development of IVOA SIAP. We discuss the requirements for extremely large SIDC, and in this light we analyse the applicability of approach taken in the ISO/IEC 15444 (JPEG2000) standards.

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arXiv2012

Astronomy and Computing: a New Journal for the Astronomical Computing Community

We introduce \emph{Astronomy and Computing}, a new journal for the growing population of people working in the domain where astronomy overlaps with computer science and information technology. The journal aims to provide a new communication channel within that community, which is not well served by current journals, and to help secure recognition of its true importance within modern astronomy. In this inaugural editorial, we describe the rationale for creating the journal, outline its scope and ambitions, and seek input from the community in defining in detail how the journal should work towards its high-level goals.

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arXiv2012

SkuareView: Client-Server Framework for Accessing Extremely Large Radio Astronomy Image Data

The new wide-field radio telescopes, such as: ASKAP, MWA, and SKA; will produce spectral-imaging data-cubes (SIDC) of unprecedented volume. This requires new approaches to managing and servicing the data to the end-user. We present a new integrated framework based on the JPEG2000/ISO/IEC 15444 standard to address the challenges of working with extremely large SIDC. We also present the developed j2k software, that converts and encodes FITS image cubes into JPEG2000 images, paving the way to implementing the pre- sented framework.

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