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The Art of Multiprocessor Programming, Second Edition, provides users with an authoritative guide to multicore programming. This updated edition introduces higher level software development skills relative to those needed for efficient single-core programming, and includes comprehensive coverage of the new principles, algorithms, and tools necessary for effective multiprocessor programming. The book is an ideal resource for students and professionals alike who will benefit from its thorough coverage of key multiprocessor programming issues.
Auteur
Maurice Herlihy received an A.B. in Mathematics from Harvard University, and a Ph.D. in Computer Science from M.I.T. He has served on the faculty of Carnegie Mellon University, on the staff of DEC Cambridge Research Lab, and is currently a Professor in the Computer Science Department at Brown University. Dr. Herlihy is an ACM Fellow, and is the recipient of the 2003 Dijkstra Prize in Distributed Computing. He shared the 2004 Gödel Prize with Nir Shavit, with whom he also shared the 2012 Edsger W. Dijkstra Prize In Distributed Computing.
Nir Shavit received a B.A. and M.Sc. from the Technion and a Ph.D. from the Hebrew University, all in Computer Science. From 1999 to 2011 he served as a member of technical staff at Sun Labs and Oracle Labs. He shared the 2004 Gödel Prize with Maurice Herlihy, with whom he also shared the 2012 Edsger W. Dijkstra Prize in Distributed Computing. He is a Professor in the Electrical Engineering and Computer Science Department at M.I.T. and the Computer Science Department at Tel-Aviv University.Victor Luchangco is a Senior Algorithms Researcher at Algorand in Cambridge, MA, USA.Professor Spear's research interests are broadly in concurrency, programming languages, and computer architecture. His goal is to make it easier for programmers to write correct, scalable applications.
Texte du rabat
Features new exercises developed for instructors using the text, with more algorithms, new examples, and other updates throughout the book Presents the fundamentals of programming multiple threads for accessing shared memory Explores mainstream concurrent data structures and the key elements of their design, as well as synchronization techniques, from simple locks to transactional memory systems
Résumé
"The book is largely self-contained, has countless examples, and focuses on what really matters. As such, it is very well suited for both a teaching environment and for practitioners looking for an opportunity to learn about this topic...The book is written in a way that makes multiprocessor programming accessible. This updated version will further confirm its status as a classic." --ComputingReviews.com, 2013
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