Data Prefetching Techniques in Computer Systems
Data Prefetching Techniques in Computer Systems, Volume 125 provides an in-depth review of the latest progress on data prefetching research. Topics covered in this volume include temporal prefetchers, spatial prefetchers, non-spatial-temporal prefetchers, and evaluation of prefetchers, with insights on possible future research direction. Specific chapters in this release include Introduction to Data Prefetching, Spatial Prefetching Techniques, Temporal Prefetching Techniques, Domino prefetching scheme, Bingo prefetching method, and The Champion prefetcher.
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Data Prefetching Techniques in Computer Systems
Data Prefetching Techniques in Computer Systems, Volume 125 provides an in-depth review of the latest progress on data prefetching research. Topics covered in this volume include temporal prefetchers, spatial prefetchers, non-spatial-temporal prefetchers, and evaluation of prefetchers, with insights on possible future research direction. Specific chapters in this release include Introduction to Data Prefetching, Spatial Prefetching Techniques, Temporal Prefetching Techniques, Domino prefetching scheme, Bingo prefetching method, and The Champion prefetcher.
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Data Prefetching Techniques in Computer Systems

Data Prefetching Techniques in Computer Systems

Data Prefetching Techniques in Computer Systems

Data Prefetching Techniques in Computer Systems

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$182.00 
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Overview

Data Prefetching Techniques in Computer Systems, Volume 125 provides an in-depth review of the latest progress on data prefetching research. Topics covered in this volume include temporal prefetchers, spatial prefetchers, non-spatial-temporal prefetchers, and evaluation of prefetchers, with insights on possible future research direction. Specific chapters in this release include Introduction to Data Prefetching, Spatial Prefetching Techniques, Temporal Prefetching Techniques, Domino prefetching scheme, Bingo prefetching method, and The Champion prefetcher.

Product Details

ISBN-13: 9780323851190
Publisher: Elsevier Science
Publication date: 02/28/2022
Series: Advances in Computers , #125
Pages: 102
Product dimensions: 6.00(w) x 9.00(h) x (d)

About the Author

Pejman Lotfi-Kamran is an associate professor of computer science, the head of the School of Computer Science, and the director of Turin Cloud Services at the Institute for Research in Fundamental Sciences (IPM). His research interests include computer architecture, computer systems, approximate computing, and cloud computing. His work on scale-out server processor design lays the foundation for Cavium ThunderX. Lotfi-Kamran has a Ph.D. in computer science from the Ecole Polytechnique Federale de Lausanne (EPFL). He received his MS and BS in computer engineering from the University of Tehran. He is a member of the IEEE and the ACM.

Hamid Sarbazi-Azad is currently a professor of computer science and engineering at Sharif University of Technology, and a research professor of computer science at the Institute for Research in Fundamental Sciences, both in Tehran, Iran . His research interests include high-performance computer/memory architectures, NoCs and SoCs, learning architectures,, social networks, and storage systems, on which he has published over 400 refereed papers. He received Khwarizmi International Award in 2006, TWAS Young Scientist Award in engineering sciences in 2007, and Sharif University Distinguished Researcher awards in years 2004, 2007, 2008, 2010 and 2013. He is now an associate editor of ACM Computing Surveys, IEEE Computer Architecture Letters, and Elsevier’s Computers and Electrical Engineering.

Table of Contents

1. Introduction to Data Prefetching
2. Spatial Prefetching Techniques
3. Temporal Prefetching Techniques
4. Domino prefetching scheme
5. Bingo prefetching method
6. The Champion prefetcher

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