| 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.
|
| Files |
| Filename |
Size |
Approximate Download Time
(Hours:Minutes:Seconds)
|
| 28.8 Modem |
56K Modem |
ISDN (64 Kb) |
ISDN (128 Kb) |
Higher-speed Access |
| |
kulshresthadiss.pdf |
3.64 Mb |
00:16:52 |
00:08:40 |
00:07:35 |
00:03:47 |
00:00:19 |
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