Instruction Level Parallelism

Name: Instruction Level Parallelism
Author: Alex Aiken|Utpal Banerjee|Arun Kejariwal|Alexandru Nicolau
ISBN: 9781493979592

Alex Aiken|Utpal Banerjee|Arun Kejariwal|Alexandru Nicolau

Language: English

Published by Springer US, 2018

1493979590 / 9781493979592

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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an unprecedented text, uniquely dedicated to Instruction Level Parallelism (ILP)Provides a detailed examination of ILP architecturesOffers practical descriptions of key sc.

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Title: Instruction Level Parallelism
Author: Alex Aiken|Utpal Banerjee|Arun Kejariwal|Alexandru Nicolau
Publisher: Springer US
Publication year: 2018
Condition: New
Binding: Soft cover
Language: English
ISBN 10: 1493979590
ISBN 13: 9781493979592

About the Author

Alex Aiken is the Alcatel-Lucent Professor and the current chair of the Computer Science Department at Stanford. His research interests include most areas of programming languages and compilers and particularly automated methods of analysis for both high performance and high reliability.

Utpal Banerjee has a PhD in mathematics from Carnegie-Mellon University and a PhD in computer science from the University of Illinois at Urbana-Champaign. He has taught at the University of Cincinnati, Arizona State University and the University of Illinois. Dr. Banerjee has served as a research staff member at Honeywell, Fairchild, Control Data and Intel corporations. His current affiliation is with the Department of Computer Science, University of California at Irvine. He has published a number of papers and books on restructuring compilers, including encyclopedia articles and a series of books on loop transformations. He is a fellow of the IEEE and a fellow of the ACM.

Arun Kejariwal is a Statistical Learning Principal at Machine Zone. He co-founded MZ Research and currently manages a team of research scientists. He is leading the research and development of novel algorithms for fraud detection, anomaly detection in security and operational data. Prior to joining Machine Zone, he was a lead in the Data Fidelity Team at Twitter and open sourced standalone R packages for anomaly detection and breakout detection. He received Ph.D. in Computer Science from UC Irvine and is a Senior Member of IEEE and ACM.

Alexandru Nicolau’s research is in the areas of Parallel Processing/ILP, and Embedded Systems/Design Automation. His interests focus on Computer Performance/power tradeoffs, parallelizing compilers, GPUs. His current work involves collaborations both within and outside UCI, most recently with researchers at Stanford, University of Michigan, UCLA, UCSD as part of a flagship NSF Expedition project, and a separate grant with UIUC. He authored over 300 peer-reviewed papers and several books. He is the Editor-in-Chief of the International Journal of Parallel Processing, and an IEEE Fellow.

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