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Introduction to EXPReS - Beyond production e-VLBI services T. Charles Yun Program Manager EXPReS Project, JIVE.

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Presentation on theme: "Introduction to EXPReS - Beyond production e-VLBI services T. Charles Yun Program Manager EXPReS Project, JIVE."— Presentation transcript:

1 Introduction to EXPReS - Beyond production e-VLBI services T. Charles Yun Program Manager EXPReS Project, JIVE

2 2006 November 21IST Helsinki, FinlandSlide #: 2 Presentation Overview Introductions: EXPReS VLBI Correlation (analysis) Some lessons and thoughts

3 2006 November 21IST Helsinki, FinlandSlide #: 3 What is EXPReS? EXPReS = Express Production Real-time e-VLBI Service The overall objective of EXPReS is to create a production- level, real-time, electronic VLBI (e-VLBI) service, in which the radio telescopes are reliably connected to the central supercomputer at JIVE in the Netherlands, via a high-speed optical-fibre communication network... - or - Make e-VLBI routine, reliable and realistic for astronomers Introduction to EXPReS

4 2006 November 21IST Helsinki, FinlandSlide #: 4 EXPReS Details EXPReS is made possible by the European Commission (DG- INFSO), Sixth Framework Programme, Contract # Project Details Three year, started March 2006 International collaboration Funded at 3.9 million EUR Means: high-speed communication networks operating in real-time and connecting some of the largest and most sensitive radio telescopes on the planet Introduction to EXPReS

5 2006 November 21IST Helsinki, FinlandSlide #: 5 Activities in EXPReS Networking Activities NA1: Management of I3 NA2: EVN-NREN Forum NA3: e-VLBI Science Forum NA4: e-VLBI Outreach, Dissemination & Communications Specific Service Activities SA1: Production e-VLBI Service SA2: Network Provision for a Global e-VLBI Array Joint Research Activities JRA1: Future Arrays of Broadband Radio Telescopes on Internet Computing Introduction to EXPReS

6 2006 November 21IST Helsinki, FinlandSlide #: 6 EXPReS Partners Joint Institute for VLBI in Europe (coordinator), the Netherlands AARNET Pty Ltd., Australia ASTRON, the Netherlands Centro Nacional de Informacion Geografica, Spain Chalmers Tekniska Hoegskola Aktiebolag, Sweden Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia Cornell University, USA Delivery of Advanced Network Technology to Europe Ltd. (DANTE), UK Instituto Nazionale di Astrofisica, Italy Instytut Chemii Bioorganicznej PAN, Poland Max Planck Gesellschaft zur Foerderung der Wissenschaften e.V., Germany National Research Foundation, South Africa Shanghai Astronomical Observatory, Chinese Academy of Sciences, China SURFNet b.v., The Netherlands Teknillinen Korkeakoulu, Finland The University of Manchester, UK Universidad de Concepcion, Chile Uniwersytet Mikolaja Kopernika, Poland Ventspils Augstskola, Latvia Introduction to EXPReS

7 2006 November 21IST Helsinki, FinlandSlide #: 7 Primer- VLBI A radio telescope looks at an object in the sky and collects data to create an image of the source Multiple telescopes can view the same object. The distance between the telescopes is the baseline. The baseline can be compared to building a single telescope with the diameter of this distance (sort of). The resolution increases with additional telescopes and longer baselines Correlation is the process by which data from multiple telescopes is collected and processed to create a more accurate image. The correlator a super computer (interferometry) The sensitivity of the image increases with the data collection rate at the telescope Introduction to VLBI

8 2006 November 21IST Helsinki, FinlandSlide #: 8 Once upon a time... Telescopes collected data on tapes… heavy and bulky… postal mail… once all the tapes arrived… tapes were lost/damaged… hard drive arrays slightly improved the situation... It was not unusual for the time between experiment to the beginning of correlation to be multiple weeks. Today, you can transport the data over the network: e-VLBI - electronic VLBI Introduction to VLBI

9 2006 November 21IST Helsinki, FinlandSlide #: 9 Why transport data over the network? Using the network to transport data improves science Eliminating the need to move physical objects enables: Real time analysis Ability to identify minor problems in data collection Hybrid observations Responsiveness to transient events Automated observation (hands-off observing) Networked data supports flexible analysis Introduction to VLBI

10 2006 November 21IST Helsinki, FinlandSlide #: 10 Primer- Correlation (Analysis) Synthesis imaging simulates a very large telescope by measuring Fourier components of sky brightness on each baseline pair EVN MkIV data processor at JIVE custom silicon, 1024 chips Input data is 1 Gb/s max Around 100 T-operations/sec Dedicated, purpose designed/built hardware Introduction to Correlation

11 2006 November 21IST Helsinki, FinlandSlide #: 11 Once upon a time… Cost to build correlator… limited flexibility (majority of computation in custom hardware)… preset data input rates… scheduling of scarce resource (correlator)… upgrade cost forces longer life-cycle than desired Introduction to Correlation

12 2006 November 21IST Helsinki, FinlandSlide #: 12 Why Grid-ify correlation? Grid computing offers promising possibilities: keep up with input (e.g., LOFAR on BlueGene) Higher precision and new applications Better sensitivity, interference mitigation, spacecraft navigation Can CPU cycles be found on the Grid? From 16 1Gb/s (eVLBI) To 1000s at 100 Gb/s (SKA) Introduction to Correlation

13 2006 November 21IST Helsinki, FinlandSlide #: 13 Lessons Learned Each of these bullets is a set of papers, posters and presentations in and of itself… Networking is coordination EXPReS participants on 6 continents Connectivity Networking assumes connectivity, Last mile issues Saturating the network is hard End host hardware End-to-end Network optimization Designing new applications Custom software- operational vs. proof of concept Flexible solutions- address current problems, future needs Reflection.

14 2006 November 21IST Helsinki, FinlandSlide #: 14 Looking Forward Much has been done before Importance of standards, open source Look at other leaders in the field Collaboration Working across disciplines, continents Partnering to fill gaps (e.g., cpu hardware, analysis algorithms, visualization, network, storage) Shared investments Reflection.

15 2006 November 21IST Helsinki, FinlandSlide #: 15 Questions/Answers Contact information T. Charles Yun Project Manager EXPReS (JIVE) tcyun \at\ jive dot nl Additional Information only one s] EXPReS is made possible through the support of the European Commission (DG-INFSO), Sixth Framework Programme, Contract # Conclusion

16 2006 November 21IST Helsinki, FinlandSlide #: 16


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