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University of Illinois at Urbana-Champaign

Automatic ARIMA Time Series Modeling and Forecasting for Adaptive Input /Output Prefetching

Abstract

dc:description

To validate our approach, we built a prototype that integrates adaptive prefetching with caching and local disk striping in the PPFS2 [51] testbed. Results obtained for a computational physics code demonstrate 30% improvement in total execution time over the traditional Unix file system on three Linux clusters, equipped with different hardware configurations. More importantly, this performance improvement has small memory requirements and is shown to scale with increasing I/O intensity.

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
  • Tran, Nancy Ngoc
Contributors dc:contributor
  • Daniel A. Reed

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI3044246
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/81603

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

Tran, Nancy Ngoc. Automatic ARIMA Time Series Modeling and Forecasting for Adaptive Input /Output Prefetching. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/81603