A GRID solution for Gravitational Waves Signal Analysis from Coalescing Binaries:A GRID solution for Gravitational Waves Signal Analysis from Coalescing Binaries:preliminary algorithms and testspreliminary algorithms and tests

F. Acernese1,2, F. Barone2,3, R. De Rosa1,2, R. Esposito2, P. Mastroserio2, L. Milano1,2, S. Pardi1, K. Qipiani2, G. Spadaccini1,2

1Dip. Scienze Fisiche, Univ. Napoli, Italy, I-80126 2INFN, sez. Napoli, Italy, I-80126 3Dip. Scienze Farmaceutiche, Univ. Salerno, Italy, I-84084

MotivationMotivation

The procedure for the extraction of gravitational wave signals coming from coalescing binaries provided by the output signal of an interferometric antenna may require computing powers generally not available in a single computing centre or laboratory. In order to overcome this problem, one of the possible solutions is that of using the computing power available in different places as a single geographically distributed computing system. This possibility is now effective within the GRID environment, that allows distributing the required computing effort for specific data analysis procedure among different sites according to the available computing power.

Within this environment we decided to develop a system prototype with application software for the first experimental tests of a geographically distributed computing system for the analysis of gravitational wave signal from coalescing binary systems. These tests have been performed within a small GRID environment based on three local nodes: the Bologna node, acting as Tier-1, and the Napoli and Roma nodes, both acting as Tier-2. The tests were aimed: 1- to get information both on the reliability and the performances of the physics application software developed for the coalescing binary analysis by the Napoli group; 2- to test the efficiency of integration special tools developed for GRID within this specific application.

MotivationMotivation

The procedure for the extraction of gravitational wave signals coming from coalescing binaries provided by the output signal of an interferometric antenna may require computing powers generally not available in a single computing centre or laboratory. In order to overcome this problem, one of the possible solutions is that of using the computing power available in different places as a single geographically distributed computing system. This possibility is now effective within the GRID environment, that allows distributing the required computing effort for specific data analysis procedure among different sites according to the available computing power.

Within this environment we decided to develop a system prototype with application software for the first experimental tests of a geographically distributed computing system for the analysis of gravitational wave signal from coalescing binary systems. These tests have been performed within a small GRID environment based on three local nodes: the Bologna node, acting as Tier-1, and the Napoli and Roma nodes, both acting as Tier-2. The tests were aimed: 1- to get information both on the reliability and the performances of the physics application software developed for the coalescing binary analysis by the Napoli group; 2- to test the efficiency of integration special tools developed for GRID within this specific application.

ConclusionsConclusions

We have successfully verified that multiple jobs can be submitted and the output retrieved with small overhead time;

Computational grids seems very suitable to perform data analysis for coalescing binaries searches.

ConclusionsConclusions

We have successfully verified that multiple jobs can be submitted and the output retrieved with small overhead time;

Computational grids seems very suitable to perform data analysis for coalescing binaries searches.

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GRIDGRID

GRID is an infrastructure that enables the integrated, collaborative use of high-end computers, networks, databases, and scientific instruments owned and managed by multiple organisations. GRID applications often involve large amounts of data and/or computing and often require secure resource sharing across organisational boundaries, and are thus not easily handled by today's Internet and Web infrastructures. Within this context the Globus project is developing fundamental technologies needed to build computational grids.

GRIDGRID

GRID is an infrastructure that enables the integrated, collaborative use of high-end computers, networks, databases, and scientific instruments owned and managed by multiple organisations. GRID applications often involve large amounts of data and/or computing and often require secure resource sharing across organisational boundaries, and are thus not easily handled by today's Internet and Web infrastructures. Within this context the Globus project is developing fundamental technologies needed to build computational grids.

Matched Filter AlgorithmMatched Filter Algorithm

It is the best procedure in searching of known waveform embedded in noise background. Despite of its optimal character,it requires a high computational cost.

In fact, this method is based on an exhaustive comparison between the signal and all the possible waveforms taken in account, called templates. If the number of templates increases, the quality of the signal identification increases but a very large number of operations is needed

Matched Filter AlgorithmMatched Filter Algorithm

It is the best procedure in searching of known waveform embedded in noise background. Despite of its optimal character,it requires a high computational cost.

In fact, this method is based on an exhaustive comparison between the signal and all the possible waveforms taken in account, called templates. If the number of templates increases, the quality of the signal identification increases but a very large number of operations is needed

StepsSteps of the procedureStep 1The data were extracted from CNAF-Bologna Mass Storage System. The extraction process reads the VIRGO standard frame format, performs a simple resampling and publishes the selected data file on the Storage Element;

Step 2The search was performed dividing the template space in 200 subspace and submitting from Napoli User Interface a job for each template subspace.

Each job reads the selected data file from the Storage Element (located at CNAF-Bologna) and runs on the Worker Nodes selected by Resource Broker in the VIRGO VO.

Finally, the output data of each job were retrieved from Napoli User Interface

StepsSteps of the procedureStep 1The data were extracted from CNAF-Bologna Mass Storage System. The extraction process reads the VIRGO standard frame format, performs a simple resampling and publishes the selected data file on the Storage Element;

Step 2The search was performed dividing the template space in 200 subspace and submitting from Napoli User Interface a job for each template subspace.

Each job reads the selected data file from the Storage Element (located at CNAF-Bologna) and runs on the Worker Nodes selected by Resource Broker in the VIRGO VO.

Finally, the output data of each job were retrieved from Napoli User Interface

Conditions of the test procedureConditions of the test procedure

Algorithm: standard matched filters Templates generated at PN order 2 with Taylor approximants Data

Data simulated at 20 kHz Each data frame is 1 second long Total data length: 600 s

 Conditions raw data resampled at 2 kHz lower frequency: 60 Hz upper frequency: 1 kHz search space: 2 – 10 solar masses minimal match: 0.97

Number of templates: ~ 40000

Conditions of the test procedureConditions of the test procedure

Algorithm: standard matched filters Templates generated at PN order 2 with Taylor approximants Data

Data simulated at 20 kHz Each data frame is 1 second long Total data length: 600 s

 Conditions raw data resampled at 2 kHz lower frequency: 60 Hz upper frequency: 1 kHz search space: 2 – 10 solar masses minimal match: 0.97

Number of templates: ~ 40000

Scheme of the computational GRID used during the testsScheme of the computational GRID used during the tests

Computing Element

Worker Node 1

Worker Node 3

Storage Element

Worker Node 2

CNAF-BolognaCNAF-Bologna

Resource Broker

Information Index

Replica Catalogue

Computing Element

Worker Node 1

Worker Node 2

User Interface

INFN Roma1INFN Roma1

Computing Element

Worker Node 1

Worker Node 2

User Interface

INFN NapoliINFN Napoli

GARR

Data

Storage Element

Storage Element

Map of the templates used in the test (tau space)Map of the templates used in the test (tau space)

Università degli Studi di Napoli “Federico II”Università degli Studi di Napoli “Federico II”

Istituto Nazionale di Fisica Nucleare - Sezione di NapoliIstituto Nazionale di Fisica Nucleare - Sezione di Napoli

Università degli Studi di SalernoUniversità degli Studi di Salerno

CHEP03 - March 24-28, 2003 - La Jolla,

California