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CAMARASU Sorina LRMN LRMN Towards a Virtual Radiological Platform Towards a Virtual Radiological Platform Based on a Grid Infrastructure Based on a Grid Infrastructure Sorina Camarasu, Hugues Benoit-Cattin, Laurent Guigues, Patrick Clarysse,


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Towards a Virtual Radiological Platform Towards a Virtual Radiological Platform Based on a Grid Infrastructure Based on a Grid Infrastructure

CAMARASU Sorina

MICCAI 2008 New York

LRMN LRMN

Sorina Camarasu, Hugues Benoit-Cattin, Laurent Guigues, Patrick Clarysse, Olivier Bernard, Denis Friboulet

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Summary Summary

Overview of the VRP Grid Contribution to the VRP Experience Feedback on Application Porting Conclusion Acknowledgments

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Overview of the VRP (I) Overview of the VRP (I)

  • Aim of the VRP

To provide realistic multi-modal medical images with ‘ground-truth’ knowledge

  • It relies on

Virtual models Medical image simulators Computer grids for data storage, computing power and sharing algorithms

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Overview of the VRP (II) Overview of the VRP (II)

  • VRP Usage
  • VRP Requirements

Simulators interoperability Easy plug-in of new simulators Making simulators accessible to everyone

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Summary Summary

Overview of the VRP Grid Contribution to the VRP Experience Feedback on Application Porting Conclusion Acknowledgments

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Why use grids behind the VRP? Why use grids behind the VRP?

  • Two major advantages/reasons

Collaborative platforms

  • The possibility to share algorithms and data

Computing power

  • The possibility to run computing intensive simulations

elsewhere than on the personal computer

  • Ex: 900 CPU hours for ‘ThIS’ (Therapeutic Irradiation

Simulator)

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Collaborative Platforms Collaborative Platforms

  • MammoGrid Project [Amendolia2005]

International mammogram database Connected sites from Udine, Geneva, Cambridge and Oxford AliEn (Alice Environment) middleware

  • The MAGIC-5 Project [Bellotti2007]

Dedicated AliEn Server Images acquired in any site available to the project Data stored on local resources and recorded on a common service (Data Catalogue), together with the related information (metadata).

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Intensive Computing and Parallelization Intensive Computing and Parallelization

  • Grid advantage: jobs can be executed in parallel

Idea: split long simulations into parallel jobs

  • Processing and/or database partitioning
  • Scalability

User scalability Multi-modality simulation => VRP usage diversity

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Summary Summary

Overview of the VRP Grid Contribution to the VRP Experience Feedback on Application Porting Conclusion Acknowledgments

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Experience Feedback on Application Porting Experience Feedback on Application Porting

  • Basic adaptability

Successful execution

  • Intermediate adaptability

Application parallelization

  • Advanced adaptability

Advanced tools for

  • Parallel job submission, monitoring and retrieval
  • Middleware compatibility
  • Integration into service platforms
  • End-User adaptability

High level interface

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Basic Adaptability Basic Adaptability

  • Aim: successful application execution on the grid worker nodes
  • Methods

Distant grid node environment customization

  • Limited access rights
  • Download input files, create folders, define

environment variables…

Application customization

  • Shared libraries non existing on the node

– Copy needed libraries with executable – Re-build dependencies and link statically

  • Results

Obtained with the application ‘ThIS’ (Therapeutic Irradiation Simulator) Static building and linking to the Geant4 and CLHEP libraries Successful execution: 5% -> 80%

ThIS Application

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Intermediate Adaptability Intermediate Adaptability

  • Aim: parallelize the application
  • Methods and examples

MPI (Message Passing Interface)

  • Transparent to the end user
  • The application can be executed on the personal computer, parallel

machines, clusters, etc.

  • Needs to be taken into account at the application development phase
  • Example: Simri (IRM Simulator)

Split the simulation into independent jobs (Monte Carlo simulations)

  • Can be done with generic tools
  • Is flexible
  • Depends on the application
  • Results

‘ThIS’ -> Monte Carlo simulator -> ~50M particles split in 100 jobs Global speed up difficult to estimate

  • Problem: failures among the 100 jobs of a same simulation
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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Advanced Adaptability Advanced Adaptability

  • Aim: automation of the submission and parallelization process
  • Methods

Grid middleware integrates basic tools

  • Submission, result retrieval…
  • Example: the WMS (Workload Management System) in gLite

More advanced tools exist

  • Java Job Submission (JJS)

– Optimized submission, but no splitting management

  • Ganga [Moscicki2004] and Diane [Maier2007]

– Splitting oriented

Wrappers for integration into a service platform

  • GEMSS project [Gemss2005] mentions application descriptors
  • Results

‘ThIS’ executed on the grid with a new master-agent approach with Ganga & Diane Global result at 100%

  • At least 3 times faster
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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

End-User Adaptability End-User Adaptability

  • Aim: a high level interface for users with no grid

knowledge

  • Methods: graphical interfaces

Web portals

  • Generic portals: Genius, GridSphere
  • Home made solutions: the Simri

portal [Bellet2006] for the Simri simulator – A 3 layer architecture portal developed in Java and PhP

  • Challenge: a more generic tool

– A portal easily re-configurable for similar applications

The Simri Portal

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Summary Summary

Overview of the VRP Grid Contribution to the VRP Experience Feedback on Application Porting Conclusion Acknowledgments

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Conclusion Conclusion

  • VRP aim

Facilitate the integration of medical simulators into the grid environment

  • Grids are VRP promising architectures

Medical imaging simulations already running on the grid

  • Grid issues still exist

Complex architectures

  • Not straightforward to use => limits the type and number of users
  • Perspectives

VRP architecture definition including WebServices and generic workflow and dataflow models

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Summary Summary

Overview of the VRP Grid Contribution to the VRP Experience Feedback on Application Porting Conclusion Acknowledgments

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Acknowledgements Acknowledgements

  • David Sarrut, Thomas Grimaldi, Fabrice Bellet
  • This research work is in the scope of the scientific topics of the

European FP7 NoE VPH and of the French National Grid Institute (IdG). This work has been partially funded by the European FP6 EGEE2 project.

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LRMN LRMN

Sorina Sorina Camarasu Camarasu, MICCAI 2008, New York , MICCAI 2008, New York

Bibliography Bibliography

  • H. Benoit-Cattin, G. Collewet, B. Belaroussi, H. Saint-Jalmes, and C. Odet, "The SIMRI project: A

versatile and interactive MRI simulator," Journal of Magnetic Resonance, vol. 173, pp. 97-115, 2005

  • The GEMSS Project: Grid-enabled medical simulation services. EU IST Project IST-2001-37153,

2002--2005, http://www.gemss.de/

  • T. Glatard, D. Lingrand, J. Montagnat, and M. Riveill, "Impact of the execution context on Grid job

performances" in International Workshop on Context-Awareness and Mobility in Grid Computing (WCAMG'07), Rio de Janeiro, 2007.

  • F. Bellet, I. Nistoreanu, C. Pera, and H. Benoit-Cattin, "Magnetic resonance imaging simulation on

EGEE grid architecture: A web portal design." in HealthGrid, Valencia, 2006, pp. 34-42

  • S. R. Amendolia,et al.,"Deployment of a Grid-based Medical Imaging Application," Stud Health

Technol Inform, 2005.

  • F. Estrella, et al., "Experiences of engineering Grid-based medical software," International journal
  • f medical informatics, pp. 621-632, 2007.
  • R. Bellotti, et al., "Distributed medical images analysis on a Grid infrastructure," Future

Generation Computer Systems, 2007

  • J. T. Moscicki, "DIANE - Distributed Analysis Environment for GRID-enabled Simulation and

Analysis of Physics Data," in NSS IEEE NSS IEEE, 2004.

  • A. Maier, et al., "Ganga - an optimiser and front-end for Grid job submission," in Second EGEE

User Forum Manchester, 2007

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Thank you for your attention! Thank you for your attention!

Questions?