2013/12/14 by Nicholas M. Ball, Ball, Nicholas M.
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #Astronomical Observations and Instrumentation #Astronomy and Astrophysical Research #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Spectroscopy Techniques in Biomedical and Chemical Research #astro-ph.IM
paper · pdf · doi:10.48550/arxiv.1312.3996
4 pages, 2 figures, uses asp2010.sty. Written when at National Research Council Canada. Now at Skytree, Inc., San Jose, CA, USA. There is a companion paper: "Focus Demo: CANFAR+Skytree: A Cloud Computing and Data Mining System for Astronomy". Astronomical Data Analysis Software & Systems (ADASS) XXII, 2012, ASP Conference Proceedings, eds. Friedel D., Freemon M., Plante R. (San Francisco: ASP)
arxiv created 2013/12/14 · openalex publication_date 2013/12/14 · arxiv updated 2013/12/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
At the Canadian Astronomy Data Centre, we have combined our cloud computing system, CANFAR, with the world's most advanced machine learning software, Skytree, to create the world's first cloud computing system for data mining in astronomy. CANFAR provides a generic environment for the storage and processing of large datasets, removing the requirement to set up and maintain a computing system when implementing an extensive undertaking such as a survey pipeline. 500 processor cores and several hundred terabytes of persistent storage are currently available to users. The storage is implemented via the International Virtual Observatory Alliance's VOSpace protocol, and is accessible both interactively, and to all processing jobs. The user interacts with CANFAR by utilizing virtual machines, which appear to them as equivalent to a desktop. Each machine is replicated as desired to perform large-scale parallel processing. Such an arrangement enables the user to immediately install and run the same astronomy code that they already utilize, in the same way as on a desktop. In addition, unlike many cloud systems, batch job scheduling is handled for the user on multiple virtual machines by the Condor job queueing system. Skytree is installed and run just as any other software on the system, and thus acts as a library of command line data mining functions that can be integrated into one's wider analysis. Thus we have created a generic environment for large-scale analysis by data mining, in the same way that CANFAR itself has done for storage and processing. Because Skytree scales to large data in linear runtime, this allows the full sophistication of the huge fields of data mining and machine learning to be applied to the hundreds of millions of objects that make up current large datasets. We demonstrate the utility of the CANFAR+Skytree system by showing science results obtained. [Abridged]