Title page for ETD etd-04202011-091322


Type of Document Dissertation
Author Kulshrestha, Archit
Author's Email Address akulsh1@lsu.edu
URN etd-04202011-091322
Title Quality of Service Based Data Aware Scheduling
Degree Doctor of Philosophy (Ph.D.)
Department Computer Science
Advisory Committee
Advisor Name Title
Allen, Gabrielle Committee Chair
Iyengar, Sitharama S. Committee Member
Kosar, Tevfik Committee Member
Mukhopadhyay, Supratik Committee Member
Mehraeen, Shahab Dean's Representative
Keywords
  • coastal modeling
  • SCOOP
  • data-aware
  • scheduling
  • grid computing
Date of Defense 2011-04-15
Availability unrestricted
Abstract
Distributed supercomputers have been widely used for solving complex computational problems and modeling complex phenomena such as black holes, the environment, supply-chain economics, etc. In this work we analyze the use of these distributed supercomputers for time sensitive data-driven applications. We present the scheduling challenges involved in running deadline sensitive applications on shared distributed supercomputers running large parallel jobs and introduce a ``data-aware'' scheduling paradigm that overcomes these challenges by making use of Quality of Service classes for running applications on shared resources. We evaluate the new data-aware scheduling paradigm using an event-driven hurricane simulation framework which attempts to run various simulations modeling storm surge, wave height, etc. in a timely fashion to be used by first responders and emergency officials. We further generalize the work and demonstrate with examples how data-aware computing can be used

in other applications with similar requirements.

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