Introduction to Grid Technologies in EGEE

1
Introduction to Grid Technologies in EGEE

• Emanouil Atanassov,
• Aneta Karaivanova and Todor Gurov
• Institute for Parallel Processing - BAS

2
Overview

• Evolvement of Grids
• What is Grid?
• Grid Services
• Goals of the EGEE project
• Building a production Grid for e-Science
• Grid applications in EGEE and SEE-GRID
• The Grid Challenges

3
Evolvement of Grids

• Historical perspective
• Local Computing
• All computing resources at single site.
• People move to resources to work.
• Remote Computing
• Resources accessible from distance.
• All significant resources still centralized.
• Distributed Computing
• Resources geographically distributed.
• Specialized access largely data transfers.
• Grid Computing
• Resources and services geographically
  distributed.
• Standard interfaces transfers of computations
  and data.
• Web Services and Grid Computing Grid Services
• Industry adopts Grid technology

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What is GRID?

• Coordinated resource sharing and problem solving
  in dynamic, multi-institutional virtual
  organizations (I.Foster)
• Resources are controlled by their owners
• The Grid infrastructure provides access to
  collaborators
• A Virtual Organization is
• People from different institutions working to
  solve a common goal
• Sharing distributed processing and data resources
• Enabling People to Work Together on Challenging
  Projects
• Science, Engineering, Medicine - e-Science,
  e-Health
• Public service, commerce - e-Government,
  e-Business
• The Grid could be the new age Internet
• The Grid intends to make access to computing
  power, scientific data repositories and
  experimental facilities as easy as the Web makes
  access to information., UK PM, 2002

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The GRID vision

• On one hand
• Researchers/employees perform their activities
  regardless of geographical location, interact
  with colleagues, share and access data
• On the other hand
• Scientific instruments and experiments provide
  huge amount of data, incl. national databases
• And in the middle
• The Grid networked data, processing centres and
  grid middleware as the glue of resources.

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Grid Services

• Basic unit of computation job
• Basic unit of storage file
• Information systems BDII, Globus-mds, R-GMA,
  file catalogues, metadata catalogues
• Authorization, authentication, accounting (AAA)
  based on PKI (Public key infrastructure)
• Every Grid site provides basic Grid services
• Advanced Grid Services MPI jobs, Mass Storage
  Facilities accessed via SRM, Fine grained AAA
  (VOMS, DGAS).

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Grid Services - schema
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Grid Services in gLite
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EGEE Partner Federations

• All work in EGEE will be carried out by the 70
  partners grouped in 12 federations.

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Goals of the EGEE project

• Goal in one sentence
• Allow scientists from multiple domains to use,
  share, and manage geographically distributed
  resources transparently.
• The EGEE project brings together experts from
  over 27 countries with the common aim of building
  on recent advances in Grid technology and
  developing a service Grid infrastructure,
  available to scientists 24 hours-a-day.
• The project aims to provide researchers in
  academia and industry with access to major
  computing resources, independent of their
  geographic location. The EGEE project will also
  focus on attracting a wide range of new users to
  the Grid.

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Scientific disciplines to run Grid applications

• EGEE aims to establish production quality
  sustained Grid services
• 3000 users from at least 5 disciplines
• integrate 50 sites into a common infrastructure
• offer 5 Petabytes (1015) storage
• Demonstrate a viable general process to bring
  other scientific communities on board

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EGEE building a production Grid for e-Science

• Operations Management Centre (OMC)
• At CERN coordination etc
• Core Infrastructure Centres (CIC)
• Manage daily grid operations oversight,
  troubleshooting
• Run essential infrastructure services
• Provide 2nd level support to ROCs
• UK/I, Fr, It, CERN, Russia (M12)
• Taipei also run a CIC
• Regional Operations Centres (ROC)
• Act as front-line support for user and operations
  issues
• Provide local knowledge and adaptations
• One in each region many distributed
• User Support Centre (GGUS)
• In FZK manage PTS provide single point of
  contact (service desk)
• Not foreseen as such in TA, but need is clear

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Components of a production Grid

• A production Grid consists of stable
  interoperating Grid sites (Resource centres),
  which enable access to Grid users from various
  Virtual Organizations
• Every Grid site provides basic Grid services and
  follows strict operational procedures.
• Monitoring allows fast detection of problems and
  their resolution or isolation.

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BG01-IPP setup
Terminals
SE
BDII
- PKI X.509 certificate keys - JDL files
RB/II
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Structure of EGEE operations

• The grid is flat, but
• Hierarchy of responsibility
• Essential to scale the operation
• CICs act as a single Operations Centre
• Operational oversight (grid operator)
  responsibility
• rotates weekly between CICs
• Report problems to ROC/RC
• ROC is responsible for ensuring problem is
  resolved
• ROC oversees regional RCs
• ROCs responsible for organising the operations in
  a region
• Coordinate deployment of middleware, etc
• CERN coordinates sites not associated with a ROC

RC Resource Centre
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Operations monitoring maps

• In LCG-2
• 137 sites, 34 countries
• gt12,000 cpu
• 5 PB storage
• Includes non-EGEE sites
• 9 countries, 18 sites

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Selection of Monitoring tools
GIIS Monitor
GIIS Monitor graphs
Sites Functional Tests
GOC Data Base
Scheduled Downtimes
Live Job Monitor
GridIce VO view
GridIce fabric view
Certificate Lifetime Monitor
Note Those thumbnails are links and are
clickable.
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Example LHC at CERN
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CMS LHC Experiment
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Example biomedical app gPTM3D

• One data set is
• DICOM files 100MB 1GB
• One radiological image 20MB 500MB
• Complex interface optimized graphics and
  medically-oriented interactions
• Physician interaction is required at and inside
  all steps
• Poorly discriminant data, pathologies, medical
  windowing

Interaction
Render
Explore
Analyse
Interpret
Acquire
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Figures
Dataset 87MB 210MB 346MB 87MB
Input data 3MB 18KB/slice 9.6
MB 25KB/slice 15MB 22KB/sclice 410KB 4KB/slice
Output data 6MB 106KB/slice 57MB 151KB/slice
86MB 131KB/slice 2.3MB 24KB/slice
Tasks 169 378 676 95
StandaloneExecution 5min15s 1min54s 33min 11min
5s 18min 36s
EGEE Execution 14 procs. 37s 18s 2min30s 1min15s
2min03 24s
Small body Medium body Large body Lungs
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Example The MAGIC Telescope

• Ground based Air Cerenkov Telescope
• Gamma ray 30 GeV - TeV
• LaPalma, Canary Islands (28 North, 18 West)
• 17 m diameter
• operation since autumn 2003(still in
  commissioning)
• Collaborators

IFAE Barcelona, UAB Barcelona, Humboldt U.
Berlin, UC Davis, U. Lodz, UC Madrid, MPI
München, INFN / U. Padova, U. Potchefstrom, INFN
/ U. Siena, Tuorla Observatory, INFN / U. Udine,
U. Würzburg, Yerevan Physics Inst., ETH Zürich
Physics Goals Origin of VHE Gamma rays Active
Galactic Nuclei Supernova Remnants Unidentified
EGRET sources Gamma Ray Burst
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Ground based ?-ray astronomy
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MAGIC Hadron rejection

• Based on extensive Monte Carlo Simulation
• air shower simulation program CORSIKA
• Simulation of hadronic background is very CPU
  consuming
• to simulate the background of one night, 70 CPUs
  (P4 2GHz) needs to run 19200 days
• to simulate the gamma events of one night for a
  Crab like source takes 288 days.
• At higher energies (gt 70 GeV) observations are
  possible already by On-Off method (This reduces
  the On-time by a factor of two)
• Lowering the threshold of the MAGIC telescope
  requires new methods based on Monte Carlo
  Simulations

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BG application in SEE-GRID VO - SALUTE

• The Problem ultra-fast semiconductor carrier
  transport
• femtosecond relaxation of hot electrons by
  phonon emission in presence of electric field.
• Barker-Ferry equation and Monte Carlo approach
• Application in nanotechnologies innovative
  results for GaAs
• collision broadening and memory effects of
  quantum kinetic model
• Intra-collision field effect quantum scattering
  - retarding and accelerating field.
• NP-hard problem concerning the evolution time
• Parallel and Grid implementation

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Wigner function
800 x 260 points 150 fs
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Energy relaxation processcollisional broadening
Accumulation From 10 fs up to 250 fs
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BG application in ESR VO air pollution
prediction

• Under development by Tzvetan Ostromsky from IPP
• Transition from HPC to Grid computing

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Challenges before new sites

• Install middleware and follow security and
  middleware upgrades in a timely fashion
• Present valuable resource to the Virtual
  Organizations that the site supports
• Participate in the various challenges. So far we
  have seen the HEP and the Biomed VO challenges,
  and the security challenges
• Participate in innovation efforts development
  of middleware and/or grid applications
• Attract new users
• The Grid is about people

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BG Grid support centre contact information

• Contact persons
• Emanouil Atanassov, SA1 Activity Leader,
• emanouil_at_parallel.bas.bg
• Aneta Karaivanova,
• NA2 Activity Leader,
• anet_at_parallel.bas.bg
• Todor Gurov,
• Alternate EGEE SEE-ROC and SEE-GRID
  manager, gurov_at_parallel.bas.bg
• Ivan Dimov,
• EGEE SEE-GRID Project manager for BG
• ivdimov_at_bas.bg

• http//www.grid.bas.bg/