enabling grid computing using easygrid/lcg

1
EasyGrid architecture: enabling an on going experiment. Easymoncar Monte Carlo Events generation Easysub Raw data analisys Easygftp Generic data access Easyapp Generic application Easyroot Root application LCG Grid middleware Enables conventional software to use grid technologies: •submission •gridification algorithms •follow up/ management •results/reports recovery Grid becomes transparent to the user. Layer between complex LCG Middleware and user application. Easy to use! Does not require Training or knowledge. Data gridification Functional gridification: Genetic Progra Dataset File-1 File-2 File-N User binary easygrid WN1 WN2 WNN LCG Results Searching anti-Deuteron: Searching anti-Deuteron: Raw data: 1,500 million events 1 week – 250 computer Tau decay in N Tau decay in N neutral pions neutral pions Monte Carlo generation: 5 million events Raw data: 482 million events. 90% of all processing done in distributed fitness evaluation: WN master WN slave WN slave WN slave easygrid PVM Discrimination background/neutral pion accuracy Discrimination background/neutral pion accuracy: Decrease in Processing time Decrease in Processing time: Stand alone 1node/2slaves 5 nodes/10slaves 80 Ksec 47 Ksec 19 Ks 58% Random Pop Init Fitness evaluation Converge? Selection crossover mutation Best individual Generations James Cunha Werner Enabling one algorithm running in several worker nodes. Discriminate function to distinguish background from real neutral pions Enabling many copies of the same binary code run in several datasets in parallel, using GRID capabilities. BaBar Experiment: US$60 million Detector installed at SLAC/ Stanford University: •Thousands of measured points for each event. •3,000 million real events (1999-2005) •3,200 million Monte Carlo events. •2,500 computers in parallel running batch system •290,000 data files •161 Tera bytes of data For more information: http://www.hep.man.ac.uk/u/jamwer Particle Physics 2006 – IoP – University of Warwick

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Enabling grid computing using easygrid/LCG. James Cunha Werner. BaBar Experiment :. US$60 million Detector installed at SLAC/ Stanford University : Thousands of measured points for each event. 3,000 million real events (1999-2005) 3,200 million Monte Carlo events. - PowerPoint PPT Presentation

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Page 1: Enabling grid computing  using easygrid/LCG

EasyGrid architecture: enabling an on going experiment.

EasymoncarMonte Carlo Events generation

EasysubRaw data analisys

EasygftpGeneric data access

EasyappGeneric application

EasyrootRoot application

LCGGrid

middleware

Enables conventional softwareto use grid technologies:

•submission•gridification algorithms•follow up/ management•results/reports recovery

Grid becomes transparent to the user.Layer between complex LCG Middleware and user application.Easy to use! Does not requireTraining or knowledge.

Data gridification Functional gridification: Genetic Programming

Dataset

File-1

File-2

File-N

User binary

easygrid

WN1

WN2

WNN

LCGResults

Searching anti-Deuteron:Searching anti-Deuteron:Raw data: 1,500 million events1 week – 250 computer

Tau decay in N Tau decay in N neutral pionsneutral pionsMonte Carlo generation: 5 million eventsRaw data: 482 million events.

90% of all processing done in distributed fitness evaluation:

WN master

WN slave WN slave WN slave easygrid PVM

Discrimination background/neutral pion accuracyDiscrimination background/neutral pion accuracy: 82%Decrease in Processing timeDecrease in Processing time:

Stand alone 1node/2slaves 5 nodes/10slaves

80 Ksec 47 Ksec 19 Ksec 58% 24%

RandomPop Init

Fitnessevaluation

Converge?

Selectioncrossovermutation

Bestindividual

Generations

James Cunha Werner

Enabling one algorithm running in several worker nodes.Discriminate function to distinguish background from real neutral pions

Enabling many copies of the same binary code run in several datasets in parallel, using GRID capabilities.

BaBar Experiment:

US$60 million Detector installed at SLAC/ Stanford University:

•Thousands of measured points for each event.

•3,000 million real events (1999-2005)•3,200 million Monte Carlo events.

•2,500 computers in parallel running batch system•290,000 data files•161 Tera bytes of data

For more information: http://www.hep.man.ac.uk/u/jamwer

Particle Physics 2006 – IoP – University of Warwick