1 / 56

Hello!

Hello!. Virtual Observatory - India. Ajit Kembhavi Inter-University Centre for Astronomy and Astrophysics Pune, India. A collaboration between IUCAA and PSPL, with a grant from the Ministry of Communications and Information Technology. The City of Pune. IUCAA.

fleur-solis
Download Presentation

Hello!

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hello!

  2. Virtual Observatory - India Ajit Kembhavi Inter-University Centre for Astronomy and Astrophysics Pune, India

  3. A collaboration between IUCAA and PSPL, with a grant from the Ministry of Communications and Information Technology

  4. The City of Pune

  5. IUCAA

  6. Persistent Systems Pvt. Ltd., Pune

  7. The Alliance Members of the IVOA

  8. Interactions

  9. The Data Avalanche • An increasing number of telescopes and large area detectors are producing immense amounts of data through imaging and spectroscopic surveys. • Terabytes of data are now available, and Petabytes will soon be available from frequent all sky imaging. • Vast databases are also being produced through simulations.

  10. Data Storage and Retrieval The Astronomer Vermeer 1632-1675 The Library of Alexandria 3rd Century BC

  11. Star Positions

  12. Stars in the Milky Way

  13. The Hertzsprung-Russell Diagram

  14. Wavelength Coverage • The data spans the electromagnetic spectrum from the radio to the gamma-ray region. • Obtaining, analysing and interpreting the data in different wavebands involves highly specialised instruments and techniques. • The astronomer needs new tools for using this wealth of data in multiwavelength studies.

  15. Virtual Observatories • Manage vast data resources and provide these on-line to astronomers and other users. • Provide tools for data analysis, visualization and mining. • Develop interoperability concepts to make different databases seamless. • Empower astronomers by providing sophisticated query and computational tools, and computing grids for producing new science.

  16. VO Schema

  17. IVOA Technology Initiatives The IVOA has identified six major technical initiatives to fulfill the scientific goal of the VO concept. IVOA-LISTS

  18. REGISTRIES: These collect metadata about about data resources and information services into a queryable database. The registry is distributed. A variety of industry standards are being investigated. • DATA MODELS: This initiative aims to define the common elements of astronomical data structures and to provide a framework to describe their relationships. • UNIFORM CONTENT DESCRIPTORS: These will provide the common language for for metadata definitions for the VO.

  19. DATA ACCESS LAYER:This provides a standardized access mechanisms to distributed data objects. Initial prototypes are a Cone Search Protocol and a simple Image Access Protocol. • VO QUERY LANGUAGE: This will provide a standard query language which will go beyond the limitations of SQL. • VOTable: This is an XML mark-up standard or astronomical tables.

  20. VO-India Projects • VOTable Parser in C++; Streaming data • Web based FITS browser • VOPlot • Plots and Statistics for VIZIER and Aladin • GALics data bases • Data mirror sites • Scientific data mining • Applications beyond astronomy

  21. VOTable • This is a new data exchange standard produced through efforts led by Francois Ochsenbien of CDS, Strasbourg and Roy Williams of Caltech. • VOTable is in XML format. Physical quantities come with sophisticated semantic information.

  22. VOTable • The format enables computers to easily parse the information and communicate it to other computers. • Federation and joining of information become possible and Grid computing is easier. • VOTable parsers have been developed in Perl, Java and C++. • Enhancements and extensions are being considered. Streaming Parser Non-streaming Parser

  23. Project Design VTable Metadata Link Collection Link Field Collection Field LinkCollection Link TableData Values minimum RowCollection maximum Row OptionCollection ColumnCollection Options

  24. The VOPLOT Collaboration Visualization and simple statistics of catalogue data. Integration with sky atlases.

  25. The VOPlot Collaboration • The idea for VOPlot was developed through a discussion between VO-I and CDS. • VOPlot was developed by PSPL and IUCAA and was integrated into Vizier with the help of CDS. • It was then decided to integrate VOPlot with Aladin, an interface was agreed on, and the integration is now complete. • The collaboration was carried through a few short visits, phone calls and E-mail. • Main persons: Sonali Kale et al (PSPL), Pierre Fernique and Francois Ochsenbien. (CDS). VOPlot

  26. FITS Manager View, create and add to FITS files Convert to other formats Fits-manager

  27. VOTable Java Streaming Writer Acts on a data array in memory to convert it to the VOTable form, Which is streamed row by row To an output file. Very large VOTables can be written without excessive memory. VOTable-Java

  28. Fast Computing • Four Alpha Server ES-45 machines • Each with 4 processors Alpha 21264C • RAM 3 x 8 Gb + 12 Gb • Fast, Low latency interconnect • Memory channel Architecture (MCA) • 1 Tera-byte SCSCI storage • Trucluster clustering environment • (Tru64 Unix, DecMPI, openMP)

  29. High Volume Storage Raid 5, 4 Terabyte

  30. Thank You

  31. IUCAA HPC Facility Hercules HPC Team : Sarah Ponthratnam Sunu Engineer Rajesh Nayak Anand Sengupta Co-proposed by : Ajit Kembhavi T. Padmnabhan Tarun Souradeep • Four Alpha Server ES-45 machines • Each with 4 processors Alpha (21264C) • 1.25 GHz clock speed • Cache on chip: 64 Kb –I, 64 Kb-D • Cache :16 Mb ECC DDR • RAM 3 x 8 Gb + 12 Gb • Fast, Low latency interconnect • Memory channel Architecture (MCA) • High volume Storage • 1 Tera-byte SCSCI • Trucluster clustering environment (Tru64 Unix, DecMPI, openMP) > 30 G flops Preliminary HPL benchmark ES-45 Specfp2000: 1327 Linpack 1000x1000: 6847

  32. Virtual Observatory - India Persistent Systems IUCAA

  33. Caltech, Fermilab, JHU, NASA/HEARC, Microsoft, NCSA/UIUC, NOAO, NRAO, Raytheon ITS, SDSC/UCSD, SAO/CXC, STScI, UPenn, UPitts/CMU, UWis, USC, USNO, USRA, CVO NVO-People

  34. Terapix Jodrell Bank

  35. Registry and DIS

  36. AVO Prototype Demo Astrogrid: Astronomy Catalogue Extractor AVO: Aladin+SED VO-India:VOPlot

  37. VOTable Data The data part in a VOTable may be represented using one of three different formats: • FITS : VOTable can be used either to encapsulate FITS files, or to re-encode the metadata. • BINARY : Supported for efficiency and ease of programming, no FITS library is required, and the streaming paradigm is supported. • TABLEDATA : Pure XML format for small tables.

  38. CVO Collaborations • There are three major projects at the CVO involving collaborations with other VO. • CVO is collaborating with the German Astrophysical VO to incorporate ROSAT X-ray data and catalogues into the CVO system. • CVO is collaborating with the Australian VO.to incorporate 2Qz and 2DF galaxy spectra into the CVO database. • CVO is an associate member of NVO and is have put in place some components of the NVO galaxy morphology demo.

  39. Science Initiatives • Many IVOA projects have active Science Working Groups consisting of astronomers from a broad cross-section of the community representing all wavelengths. • The focus here is to develop a clear perception of the scientific requirements of a VO. • Projects within the working groups will develop new capabilities for VO based analysis. • This will enable the community to create new research programs and to publish their data and research in a more pervasive and scientifically useful manner.

  40. Australian –VO Collaborations • The distributed volume renderer (dvr) software, is a tool for rendering large volumetric data sets using the combined memory and processing resources of Beowulf like clusters. • A collaboration between the Melbourne site of Aus-VO and AstroGrid aims to develop the existing dvr software into a grid-based volume rendering service. • Users will be able to select FITS-format cubes from a number of "Data Centres",have the data transferred to a chosen rendering cluster, and then proceed to visualise the volume of data remotely (See Demo).

  41. C++ VOTable Parser Motivation: • Provide a library for API based access to VOTable files. • APIs can be directly used to develop VOTable applications without having to do raw VOTable processing.

  42. C++ VOTable Parser Salient Features: • Implemented as a wrapper over XALAN-C++. • XALAN-C++ is a robust implementation of the W3C recommendations for XSL Transformations (XSLT) and the XML Path language (XPath). • XPath queries can be used to access the VOTable data.

  43. C++ VOTable Parser • Initial version - Released on May 31st , 2002. - Support only for reading of tables. - Support only for pure-XML TABLEDATA and not for BINARY or FITS data streams. - Runs on Windows NT 4.0, Windows 2000 and RedHat Linux 7.1. • Future enhancements - Can be incorporated quickly and efficiently.

  44. Parser Design Class Details • VTable: In memory representation of a single <TABLE> from the <RESOURCE> element in VOTable • TableMetaData: Contains MetaData (Fields, Links and Description) • Resource:Represents the <RESOURCE> element in the VOTable. • TableData: Contains Rows • Field: Representation of <FIELD> from VOTable • Row: Representation of <TR> from VOTable • Column: Representation of <TD> from VOTable

More Related