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| Paper: |
TensorFit: A Tool to Analyze Spectral Cubes in a Tensor Mode |
| Volume: |
522, Astronomical Data Analysis Software and Systems XXVII |
| Page: |
53 |
| Authors: |
Farias, H.; Solar, M.; Nunez, C. |
| Abstract: |
As it is already known the modern observatories like Atacama Large Millimeter/submillimeter Array (ALMA) and Very Long Baseline Array (VLBA) generate large scale data that will be accentuated with the incorporation of new observatories as the Square Kilometre Array (SKA), projecting that by 2020 we will have archived astronomical data in a PB-Scale (≈ 60 petabyte). The Chilean Virtual Observatory (ChiVO) has stored the spectral cubes of ALMA and seeks to offer these data openly to the community, both to download and process this data in his facilities. To this end our proposal considers the cubes as a high order tensor, specifically 3-way tensor with 2 spatial dimensions (galactic latitude and longitude) and a velocity dimension. This opens a new approach and opportunity for computational prohibitive massive analysis of these cubes. On this premise we propose TensorFit, a natural and scalable library to handle spectral cubes in a tensor mode. Our implementation is built on frameworks oriented to parallel and distributed processing of n-arrays on Pytorch (GPU). To verify the impact of our proposal, we focus on showing the benefits of tensor compression, in particular to tucker implementations, which has demonstrated outstanding results of super-compression of multidimensional data in other scientific domains. |
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