Scalable desktop visualisation of very large radio astronomy data cubes |
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| Institution: | 1. Department of Computer Science, University of Cape Town, Private Bag X3, 7701 Cape Town, South Africa;2. Astrophysics, Cosmology and Gravity Centre (ACGC), Department of Astronomy, University of Cape Town, Private Bag X3, 7701 Cape Town, South Africa;1. Yunnan Observatories, Chinese Academy of Sciences (CAS), P.O. Box 110, 650011 Kunming, PR China;2. Key Laboratory for the Structure and Evolution of Celestial Objects, Chinese Academy of Sciences, 650011 Kunming, PR China;3. Graduate Institute of Astronomy, National Central University, Taiwan;4. Department of Physics, National Central University, Taiwan;5. Department of Physics, Yunnan University, 650091 Kunming, Yunnan province, PR China;6. Department of Physics, Yuxi Normal University, 653100 Yuxi, Yunnan province, PR China;7. National Astronomical Research Institute of Thailand, 191 Siriphanich Bldg., Huay Kaew Rd., Chiang Mai 50200, Thailand;1. School of Physics, Korea Institute for Advanced Study, 85 Hoegi-ro, Dongdaemun-gu, Seoul 130-722, Republic of Korea;2. Center for Advanced Computation, Korea Institute for Advanced Study, 85 Hoegi-ro, Dongdaemun-gu, Seoul 130-722, Republic of Korea;1. College of Graduate Studies, University of South Africa, PO Box 392, Unisa, 0003 Pretoria, South Africa;2. Institute of Astronomy with NAO, Bulgarian Academy of Sciences, blvd. Tsarigradsko chaussee 72, Sofia 1784, Bulgaria;3. Izmir Turk College Planetarium, 8019/21 sok., No: 22, ?zmir, Turkey;1. School of Studies in Physics & Astrophysics, Pt. Ravishankar Shukla University, Raipur (C.G.) 492010, India;2. Indian Institute of Astrophysics, Koramangala, Bangalore 560034, India;1. Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel;2. Institute of Astronomy and Astrophysics, Academia Sinica, Taipei 106, Taiwan |
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| Abstract: | Observation data from radio telescopes is typically stored in three (or higher) dimensional data cubes, the resolution, coverage and size of which continues to grow as ever larger radio telescopes come online. The Square Kilometre Array, tabled to be the largest radio telescope in the world, will generate multi-terabyte data cubes – several orders of magnitude larger than the current norm. Despite this imminent data deluge, scalable approaches to file access in Astronomical visualisation software are rare: most current software packages cannot read astronomical data cubes that do not fit into computer system memory, or else provide access only at a serious performance cost. In addition, there is little support for interactive exploration of 3D data.We describe a scalable, hierarchical approach to 3D visualisation of very large spectral data cubes to enable rapid visualisation of large data files on standard desktop hardware. Our hierarchical approach, embodied in the AstroVis prototype, aims to provide a means of viewing large datasets that do not fit into system memory. The focus is on rapid initial response: our system initially rapidly presents a reduced, coarse-grained 3D view of the data cube selected, which is gradually refined. The user may select sub-regions of the cube to be explored in more detail, or extracted for use in applications that do not support large files. We thus shift the focus from data analysis informed by narrow slices of detailed information, to analysis informed by overview information, with details on demand. Our hierarchical solution to the rendering of large data cubes reduces the overall time to complete file reading, provides user feedback during file processing and is memory efficient. This solution does not require high performance computing hardware and can be implemented on any platform supporting the OpenGL rendering library. |
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| Keywords: | Methods: data analysis Techniques: miscellaneous Visualisation |
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