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What is Data Prefetching

Handbook of Research on Scalable Computing Technologies
Anticipated reading of data elements according to the forecasted execution patterns, aiming at reducing the access latency.
Published in Chapter:
On Application Behavior Extraction and Prediction to Support and Improve Process Scheduling Decisions
Evgueni Dodonov (University of Sao Paulo - ICMC, Brazil) and Rodrigo Fernandes de Mello (University of Sao Paulo - ICMC, Brazil)
Copyright: © 2010 |Pages: 16
DOI: 10.4018/978-1-60566-661-7.ch015
Abstract
The knowledge of application behavior allows predicting their expected workload and future operations. Such knowledge can be used to support, improve and optimize scheduling decisions by distributing data accesses and minimizing communication overheads. Different techniques can be used to obtain such knowledge, varying from simple source code analysis, sequential access pattern extraction, history-based approaches and on-line behavior extraction methods. The extracted behavior can be later classified into different groups, representing process execution states, and then used to predict future process events. This chapter describes different approaches, strategies and methods for application behavior extraction and classification, and also how this information can be used to predict new events, focusing on distributed process scheduling.
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