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University of Illinois at Urbana-Champaign
Automatic ARIMA Time Series Modeling and Forecasting for Adaptive Input /Output Prefetching
Abstract
dc:descriptionTo 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 × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3044246
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81603