Data Prefetching Techniques in Computer Systems

ISBN 10: 0323851193 / ISBN 13: 9780323851190

Editore: Elsevier Science Feb 2022, 2022

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This item is printed on demand - it takes 3-4 days longer - Neuware -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. 102 pp. Englisch.

Codice articolo 9780323851190

Dati bibliografici

• Titolo: Data Prefetching Techniques in Computer Systems
• Editore: Elsevier Science Feb 2022
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 0323851193
• ISBN 13: 9780323851190
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 229 L x 152 A x 8 P (millimetri) 229 millimetri di larghezza per 152 millimetri di altezza per 8 millimetri di profondità
• Peso: 308 grammi

Descrizione articolo

Riassunto

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.

• Provides accurate reviews of various topics in data prefetching
• Includes useful graphic materials to facilitate understanding of topics
• Presents the latest insights and future perspectives on covered data prefetchers

Informazioni sugli autori

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.