plan of the talk: computational issues computing model introduction to grid computing

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All-sky search for continuous gravitational waves: tests in a grid environment Cristiano Palomba INFN Roma1 Plan of the talk: Computational issues Computing model Introduction to grid computing All-sky search Tests of the all-sky Hough Transform on the grid Conclusions and next steps Mathematics of Gravitation II Warsaw, International Banach Center, 1 st -10 th September 2003

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All-sky search for continuous gravitational waves: tests in a grid environment Cristiano Palomba INFN Roma1. Plan of the talk: Computational issues Computing model Introduction to grid computing All-sky search - PowerPoint PPT Presentation

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Page 1: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search for continuous gravitational waves: tests in a grid environment

Cristiano PalombaINFN Roma1

Plan of the talk:• Computational issues • Computing model• Introduction to grid computing• All-sky search• Tests of the all-sky Hough Transform on the grid• Conclusions and next steps

Mathematics of Gravitation II Warsaw, International Banach Center, 1st-10th September 2003

Page 2: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Computational issues

The full-sky search for periodic sources of gravitational waves is computationally very demanding and needs large (distributed) computational resources. We want to explore a portion of the parameter space as large as possible. For a full-sky hierarchical search (i.e. source position completely unknown), with signal frequency up to 2kHz and a minimum source decay time t~10^4 years a computing power of the order, at least, of 1Tflop is required(see Sergio Frasca’s talk). Low granularity: the whole data analysis problem can be divided in several smaller and independent tasks, for instance dividing the frequency band we want to explore in small subsets.

Page 3: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Computing model

The analysis fits well in a distributed computing environment.

detector dataComputing environment events

We are following two approaches:Standard master/slaves farm: based on PBS, managed by a SupervisorGrid computing: geographically distributed farms, job distribution managed by a Resource Broker

Page 4: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Introduction to grid computing

• A grid is a collaborative set of computing, data storage and network resources, belonging to different administrative domains.

Mini Computer

Microcomputer

Cluster

mainframe

The classical view……

• It enables the coordinated and coherent use of largely distributed resources in a complete transparent way for the user.

(by Christophe Jacquet)

… and the new one…..

Page 5: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Introduction to grid computing: some of the major projects

European DataGrid (EDG): 2001-2003 - www.edg.org

LHC Computing Grid (LCG): 2002-2008-… - cern.ch/lcg

CrossGrid: 2002-2005 – www.crossgrid.org

DataTAG: 2002-2003 – www.datatag.org

GriPhyN – www.griphyn.org

PPDG – www.ppdg.net

iVDGL – www.ivdgl.org

TERAGRID (NSF) – www.teragrid.org

Page 6: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Introduction to grid computing: EDG (I)

Purpose: to build on the emerging grid technologies to develop a sustainable computing model for effective share of computing resources and dataMain partners:CERN - International (Switzerland/France)CNRS – FranceESA/ESRIN – International (Italy)INFN – ItalyNIKHEF – The NetherlandsPPARC - UK

Page 7: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Introduction to grid computing: EDG (II)

Assistant partners

Industrial PartnersDatamat (Italy)IBM-UK (UK)CS-SI (France)

Research and Academic InstitutesCESNET (Czech Republic)Commissariat à l'énergie atomique (CEA) – FranceComputer and Automation Research Institute,  Hungarian Academy of Sciences (MTA SZTAKI)Consiglio Nazionale delle Ricerche (Italy)Helsinki Institute of Physics – FinlandInstitut de Fisica d'Altes Energies (IFAE) - SpainIstituto Trentino di Cultura (IRST) – ItalyKonrad-Zuse-Zentrum für Informationstechnik Berlin - GermanyRoyal Netherlands Meteorological Institute (KNMI)Ruprecht-Karls-Universität Heidelberg - GermanyStichting Academisch Rekencentrum Amsterdam (SARA) – NetherlandsSwedish Research Council - Sweden

Page 8: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Introduction to grid computing: EDG basics (I)

Request

ResultRequest

Data

Client (User Interface)

Application Server (Computing Element: Gatekeeper+ Worker Nodes)

Data Server (Storage Element)

Basic Services: Resource Broker, Information Service, Replica Catalog

Page 9: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

OS & Net services

Applications

Introduction to grid computing: EDG basics (III)

Basic Services

High level Grid Middleware

Fabric management: farm installation, configuration, management, monitoring, ‘gridification’,…

Based on Globus 2.0Authentication, authorization: based on X.509 public key certificates. gridFTP: tool for secure and efficient file transfer.

Replica Catalog: resolution of logical file names into physical file names. MDS: publish information about grid resources. Condor-G: job scheduler

Resource Broker: matchmaking between job requirements and available resources.

Job submission system: wrapper for Condor-G; uses JDl scripts. Information Index: collects information concerning grid resources; read by the RB. Logging & Bookkeeping: stores information about the status and history of submitted jobs Replica Manager, GDMP: tools for creation and management of file replicas

Virgo Data Analysis Software

Page 10: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Gatekeeper

Worker Node 1

Worker Node 2

Worker Node 3

Storage Element

Gatekeeper

Worker Node 1

Worker Node 1

Gatekeeper

Worker Node 1

Worker Node 1

Introduction to grid computing: Job submission mechanismUser Interface

PBS

ResourceResource BrokerBroker I II I

IS

IS

OS

OS

L&B

Page 11: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search: all-sky Hough Transform

• It is the first incoherent step in the hierarchical procedure for the search of periodic signals.

• It is the ‘heaviest’ step, because it works on the whole parameter space to be explored.

• It has been implemented using look-up tables (LUT). This has shown to be the most efficient way.

A LUT is a C array containing the coordinates of all the points of all the circles that can be drawn for a given source frequency.Several simmetries can be exploited when building a LUT.In particular, a LUT can be used for a range of frequencies of the order, at least, of the Doppler band for the initial one.The time needed to build the LUT is negligible respect to the time needed for building the Hough Maps.

Page 12: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search: all-sky Hough Transform (II)

Page 13: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search: implementation on the grid

1. The f-t peak-map, containing the list of peaks for each time slice, is produced from the SFDB;

2. The peak-map is split in several frequency sub-bands, depending on the number of available nodes; each sub-band will be processed by one Worker Node;

E.g.: assuming we have 100 nodes, the band 500-2000Hz could be divided in 1000 sub-bands, 1.5Hz each each processor will process 5 of these

3. These input files are distributed among the Storage Elements

4. Several ‘packets’ of jobs are submitted from the User Interface: each packet will be executed on a Worker Node using one of the above input files; Each packet will consist of about 1500 jobs

4a. Each job extracts from the input file a Doppler band around the current reference frequency and calculates the HT;

Each job will last about 30 min (in case of crash only the last short job will be restarted); The LUT will be re-calculated about 8 times for each input file

Page 14: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

5. The candidates (position, frequency and spin-down values) are stored in a file; the files are replicated among Storage Elements; About 10^9 candidates will be selected after the first incoherent step

All-sky search: implementation on the grid (II)

6. Steps 1-5 are repeated for the second observation period

All subsequent steps do not need a distributed computing environment

Page 15: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search: Test of the Hough Transform on the Grid

Three sites involved.

ROMA

NAPOLI

BOLOGNA

26 processors used.

Page 16: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search: Test of the Hough Transform on the Grid - description

• test-1: intensive job submission Hundreds of jobs are submitted sequentially on the grid Targets:

- measure the performances (time needed to complete the jobs) - measure the reliability (fraction of dead jobs)

- measure the overhead time due to the RB activity - check the homogeneity in the distribution of jobs

• test-2: submission of packets of jobs Several ‘packets of jobs’ are submitted on the grid Targets:

- measure the performances (expected lower overhead?) - measure the reliability (expected lower fraction of dead

jobs)

Each job calculates the Hough Transform for a single initial source frequency.

Page 17: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

All-sky search: Test of the Hough Transform on the Grid - results

Death rate ~ 3/1000 Death rate < 1/1000

Page 18: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Conclusions

• Emerging grid technologies appear to be very effective in data analysis for the search of periodic gravitational signals.

• Our data analysis method can be very easily adapted to work on a computing grid.• Other kinds of search for gravitational signals can benefit from grid (e.g. coalescing binaries). • Soon we will pass from tests to production.

• Grid software is more and more robust and reliable.

Page 19: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

The European DataGrid project (EDG) is a EU funded project which has been started mainly to answer the computing needs of future LHC experiments. It has produced since now several software releases, which enable the ‘gridification” of a local cluster of computers.

DIFFERENZE RISPETTO, PER ES., A CONDOR, SETI ECC.

Page 20: Plan of the talk:  Computational issues   Computing model  Introduction to  grid  computing

Introduction to grid computing: EDG basics (II)

Different kind of services:

• Information Service: gives information about the availability of services on the grid (e.g. X cpu and Y GB of disk space are available at a given site)

• Authentication & Authorization: allow a user to log on the grid and use its resources

• Job submission service: responsible for the job submission according to the user needs/requests and the available resources

• Replica Management: responsible for the management of file replicas

• Logging & Bookkeeping: