High-Performance Grids and Clusters

  • Pethuru Raj
  • Anupama Raman
  • Dhivya Nagaraj
  • Siddhartha Duggirala
Part of the Computer Communications and Networks book series (CCN)


Data is generated exponentially. And data is used to identify and understand people, things, physical principles, etc. But with this much comes the problem of how to crunch the data to get our insights. With the traditional monolithic environment, crunching this huge volume will take hours and days, billing us some million dollars. But with the principle of dividing the job into smaller tasks and distributing the jobs between different computers which are interconnected, this insight could be reached within minutes to hours, costing us just a fraction of the amount. The scope of clusters and grids is vastly different. The clusters are generally employed with the locally interconnected systems, whereas grids are employed at a much wider and distributed scale. In this chapter we will learn more about these two interconnected paradigms and study some use cases.


Graphic Processing Unit Grid Computing Message Passing Interface Grid Environment Grid Service 
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Further Reading

  1. Pearce SE, Venters W (2012) How particle physicists constructed the world’s largest grid: a case study in participatory cultures. The Routledge Handbook of Participatory CulturesGoogle Scholar
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  3. Kirk DB, Wen-mei WH (2012) Programming massively parallel processors: a hands-on approach. NewnesGoogle Scholar
  4. Kahanwal D, Singh DT (2013) The distributed computing paradigms: P2P, grid, cluster, cloud, and jungle. arXiv preprint arXiv:1311.3070Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Pethuru Raj
    • 1
  • Anupama Raman
    • 1
  • Dhivya Nagaraj
    • 1
  • Siddhartha Duggirala
    • 2
  1. 1.IBM IndiaBangaloreIndia
  2. 2.Indian Institute of TechnologyIndoreIndia

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