ChiVO at SPIE Astronomical Telescopes + Instrumentation 2016
SPIE is a not-for-profit international professional society for optics and photonics technology, founded in 1955. It organizes technical conferences, trade exhibitions, and continuing education programs for researchers and developers in the light-based fields of physics, including, but not limited to: optics, photonics, and imaging engineering.
This year, Mauricio Solar was invited to give an oral presentation summarized in the following article:
Cloud services on an astronomy data center
Author(s): Mauricio Solar, Mauricio Araya, Humberto Farias, Diego Mardones, and Zhong Wang.
The research on computational methods for astronomy performed by the first phase of the Chilean Virtual Observatory (ChiVO) led to the development of functional prototypes, implementing state-of-the-art computational methods and proposing new algorithms and techniques. The ChiVO software architecture is based on the use of the IVOA protocols and standards. These protocols and standards are grouped in layers, with emphasis on the application and data layers, because their basic standards define the minimum operation that a VO should conduct. As momentary verification, the current implementation works with a set of data, with 1 TB capacity, which comes from the reduction of the cycle 0 of ALMA. This research was mainly focused on spectroscopic data cubes coming from the cycle 0 ALMA's public data. As the dataset size increases when the cycle 1 ALMA's public data is also increasing every month, data processing is becoming a major bottleneck for scientific research in astronomy. When designing the ChiVO, we focused on improving both computation and I/ O costs, and this led us to configure a data center with 424 high speed cores of 2,6 GHz, 1 PB of storage (distributed in hard disk drives-HDD and solid state drive-SSD) and high speed communication Infiniband. We are developing a cloud based e-infrastructure for ChiVO services, in order to have a coherent framework for developing novel web services for on-line data processing in the ChiVO. We are currently parallelizing these new algorithms and techniques using HPC tools to speed up big data processing, and we will report our results in terms of data size, data distribution, number of cores and response time, in order to compare different processing and storage configurations. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.