LOFAR DEEP FIELDS. CHALLENGES AND CLOUD SOLUTIONS.

Transcription

1 LOFAR DEEP FIELDS. CHALLENGES AND CLOUD SOLUTIONS. Jose Sabater Montes Institute for Astronomy, University of Edinburgh P. Best, S. Sanchez, J. Garrido, J. E. Ruiz, L. Verdes-Montenegro and the LOFAR collaboration

2 Outline LOFAR; Low Frequency Array Surveys KSP: ELAIS-N1 Challenges Cloud solutions Summary

3 LOFAR Low Frequency Array Software defined radio-interferometer working at low frequencies (30 to 240 MHz) One of the Square Kilometre Array pathfinders

4 LOFAR Stations

5 LOFAR Stations

6 LOFAR frequencies LBA MHz HBA MHz

7 LOFAR Low Frequency Array Software defined radio-interferometer Analogue to digital conversion Digital filtering and processing Simultaneous bandwidth of 96 MHz

8 LOFAR Surveys KSP Science: AGN, clusters, star formation, etc. Three tiers: Tier-1 all Northern sky; ~100 μjy Tier-2 selected fields; selected areas. Tier-3 a couple of fields; ~10 μjy 5 sigma detection limit. Norris et al. 2013

9 Blank field surveys, ELAIS-N1 Tier-2 and 3 fields with legacy multi-wavelength data: XMM-LSS, COSMOS Herschel ATLAS, Groth strip, Bootes, GOODSNorth, North Ecliptic Pole, Lockman Hole ELAIS-N1

10 Blank field surveys, ELAIS-N1 ELAIS-N1: 200 hours observed so far ~100 TB

11 LOFAR aperture synthesis field of view diameter of ~6 deg at 150 MHz resolution < 5 arcsec

12 LOFAR imaging r.m.s. 300 microjy In 10 hours Calibration on IAA (Granada) cluster

13 LOFAR imaging r.m.s. 300 microjy In 10 hours Calibration on IAA (Granada) cluster

14 Challenges Effect of the ionosphere new calibration strategies User data calibration 10 hours full resolution ~20 TB Minimum of 2 CPU years to run the calibration Experimental pipeline LOFAR calibration software Difficult to install Continuous development

15 Ionosphere Video ionosphere

16 Calibration pipeline example. Data

17 Calibration pipeline example. Data Frequency (νn) (...) (ν4) (ν3) (ν2) (ν1) (ν0)

18 Calibration pipeline example. Data (ν(ν,t) ) n nm (...) (ν(νn,tn)2) (ν4),t) ) (ν3) (...)(ν(ν nn1 Frequency (ν4) (ν2) (...)(ν(νn,tn)0) (ν ) (ν3) (ν1) (...) 4 (ν(ν4,t4)0) (ν ) (ν2) (ν0) 3 (ν(ν3,t3)0) (ν2) (ν1) (ν(ν2,t2)0) (ν1) (ν0) (ν(ν1,t1)0) (ν0) (ν(ν0,t0)0) e tim

19 Calibration pipeline example. Data (ν(ν,t) ) n nm (...) (ν(νn,tn)2) (ν4),t) ) (ν3) (...)(ν(ν nn1 Frequency (ν4) (ν2) (...)(ν(νn,tn)0) (ν ) (ν3) (ν1) (...) 4 (ν(ν4,t4)0) (ν ) (ν2) (ν0) 3 (ν(ν3,t3)0) (ν2) (ν1) (ν(ν2,t2)0) (ν1) (ν0) (ν(ν1,t1)0) (ν0) (ν(ν0,t0)0) e tim

20 Calibration pipeline example. Pipeline Calibrator data Pre-processing Calibration solutions Pre-processing Calibration Final image 360 chunks (1 sb) Main target data 36 chunks (10 sb) Combine data: 9 chunks (40 sb) ~20 iterations Final calibrated data

21 Facet self-calibration

22 Computational solution needed Parallelizable: Deal with a large amount of data in a reasonable time. Flexible: Adapt the infrastructure ( hardware ) to different calibration strategies Deal with quickly changing temperamental software On-demand (optional but very useful)

23 Cloud computing Infrastructure as a Service (IaaS) Tests on: Ibercloud EGI Federated Cloud Amazon Web Services RAL cloud

24 Ibercloud Based on OpenStack Very easy to use Discontinued and integrated on EGI Federated Cloud

25 EGI Federated Cloud Heterogeneous infrastructure (access using OCCI) Complex documentation Site dependent issues Blocker: No block storage implemented Many resources and providers Good support Difficult to use:

26 AWS SKA-AWS astrocompute proposal Very easy to use: Good documentation Big set of useful tools (computing, object and block storage, data transfer, etc.) On-demand and pay as you go - no special arrangements needed - ideal for a final user It can be expensive See

27 AWS: Data transfer 50 TB from the GRID to us-east-1 region: ~ 2 months Lot of manual supervision: GRID proxy renewal, data staging from magnetic tapes, failed downloads, etc. Consider AWS Import/Export Snowball 10 Gbps network connection and 50 TB in a box.

28 RAL Cloud Based on OpenNebula (neither specially difficult nor easy to use) Complex generation of the VM templates (human intervention, prone to errors) Good support Storage? It works Production run?

29 Summary LOFAR already producing data. For example, ELAIS-N1 field TB to date. New calibration strategies. Useful for SKA. Big software and data managing challenges associated to a software defined radio-telescope. Cloud infrastructure to calibrate astronomical data: Parallellization Ability to deal with big data. Flexibility Quick development and testing of innovative strategies and on-demand consumption of (shared) resources.