A Network-Aware Grid for Efficient Parallel Monte Carlo Simulation of Coagulation Phenomena

  • M. Marchenko
  • D. Adami
  • C. Callegari
  • S. Giordano
  • M. Pagano
Conference paper


Remote instrumentation services often rely on distributed control and computation. In this framework, a grid infrastructure offers the opportunity to utilize massive memory and computing resources for the storage and processing of data generated by scientific equipment. The provision of grid-enabled remote instrumentation services is also a key challenge for high-speed next generation networks and cross-layer mechanisms, between grid middleware and network protocols, should be introduced to support quality of service (QoS) both at network and at application layers. This chapter is mainly focused on distributed data computation and, more in detail, on the optimization of the time necessary to perform a simulation concerning particles coagulation phenomena. Extensive computations have been performed in a cluster environment and the collected data have been used as a starting point for the dimensioning of a proper grid infrastructure. Since computations are characterized by frequent data exchanges, this chapter investigates how bandwidth allocation affects overall performance.


DSMC GNRB Dynamic resource allocation MPLS-TE 



The work was supported by RFBR grants No. 06-01-00586 and No. 06-01-00046, President grant No. 587.2008.1 of “Leading scientific schools” program, INTAS grant No. 05-109-5267, Russian Science Support Foundation grant, RINGRID EU FP6 Project.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • M. Marchenko
    • 1
  • D. Adami
    • 2
  • C. Callegari
    • 3
  • S. Giordano
    • 3
  • M. Pagano
    • 3
  1. 1.Institute of Computational Mathematics and Mathematical Geophysics SB RASNovosibirskRussia
  2. 2.CNIT Research Unit, Department of Information EngineeringUniversity of PisaPisaItaly
  3. 3.Department of Information EngineeringUniversity of PisaPisaItaly

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