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University of Illinois at Urbana-Champaign

Automatic Parallel Input/output Performance Optimization in Panda

Abstract

dc:description

Finally, we must devise proper optimization strategies to search for optimal parameter settings. We present two optimization strategies in this thesis, a rule-based strategy and a simulated annealing-search algorithm. We show that with proper use of these strategies, the Panda performance model can be used to select high quality parameter settings for a wide spectrum of system conditions with a low optimization overhead. (Abstract shortened by UMI.).

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chen, Ying
Contributors dc:contributor
  • Winslett, Marianne

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI9904407
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/81914

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Chen, Ying. Automatic Parallel Input/output Performance Optimization in Panda. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/81914