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LIGO DATA GRID

archive. Interferometer. Short time frames. Long time frames. clean. transpose. raw channels. Single Frame. Time-frequency. Image. Hz. Find Candidate. event. DB. Store. Time. Initial Prototype Logic. •. Parse Application’s Request. •. Map request to a series of 10 second frame.

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LIGO DATA GRID

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  1. archive Interferometer Short time frames Long time frames clean transpose raw channels Single Frame Time-frequency Image Hz Find Candidate event DB Store Time Initial Prototype Logic • Parse Application’s Request • Map request to a series of 10 second frame files (logical file names) • For each logical file – check the existence of file in RC – if file exists, retrieve from “closest location” – otherwise request file from HPSS via LARS • construct LARS query • retrieve resulting file and store on local storage and register new file with Replica Catalog • Merge desired frame files • Place Result in Temporary Storage • Return URL to application LIGO DATA GRID K. Blackburn†, S. Chouksey‡, E. Deelman‡, C. Kesselman‡, A. Lazzarini†, P. Shawhan†, R. Williams† Caltech, ‡ISI LIGO Overview • Aims to detect gravitational waves predicted by Einstein’s theory of relativity. • Can be used to detect – binary pulsars – mergers of black holes – “ starquakes ” in neutron stars • Two installations: in Louisiana and Washington State • Instruments are designed to measure the effect of gravitational waves on test masses suspended in vacuum. • Data collected during experiments is a collection of time series (multi-channel) • Analysis is performed in time and Fourier domains Virtual Data Scenario Data in LIGO • Request: Seismometer channels for 3 days in April 2000 • All data stored on HPSS at Caltech (Currently frames can be requested using the LIGO LARS software and protocol) • Four centers around the country (future) • For each requested data value, need to • Other collaborators will store subsets of the data – Determine if it is instantiated; if so, where; if not, how to compute it • Need to know where the data is located – Plan data movements and computations required to • If the data was already computed, might not be efficient obtain all results to recompute – Execute this plan Desired Result : Power spectrum of seismic channels P. Charlton LIGO Application Channel, start time, stop time Virtual Data URL Request Manager Replica Selection Replica Management existing GriPhyN Architecture for Prototype in development LARS Prot. LDAP GridFTP FTP planned Connectivity “local” storage HPSS at Caltech Other Remote Storage Replica Catalog Transfor- mation Catalog Derived Data Catalog GriPhyN LARS and/or GridFtp HPSS Transformation Catalog Replica Catalog Hanford Modified LARS Request Request Manager LDAS Replica Mgmt. Local Storage ftp and/or GridFtp Derived Data Catalog Reference: E. Deelman, C. Kesselman, R. Williams, A. Lazzarini, T. A. Prince, J. Romano and B. Allen , A Virtual Data Grid for LIGO Proc. HPCN Europe 2001, Amsterdam, June 25-27 (to appear)

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