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The Art of Multiprocessor Programming, Revised Reprint


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Update of the best-selling multicore programming text with more than 100 pages of updates in response to reader feedback

Table of Contents

1. Introduction 2. Mutual Exclusion 3. Concurrent Objects and Linearization 4. Foundations of Shared Memory 5. The Relative Power of Synchronization Methods 6. The Universality of Consensus 7. Spin Locks and Contention 8. Monitors and Blocking Synchronization 9. Linked Lists: the Role of Locking 10. Concurrent Queues and the ABA Problem 11. Concurrent Stacks and Elimination 12. Counting, Sorting and Distributed Coordination 13. Concurrent Hashing and Natural Parallelism 14. Skiplists and Balanced Search 15. Priority Queues 16. Futures, Scheduling and Work Distribution 17. Barriers 18. Transactional Memory Appendices

About the Author

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 Goedel 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 Goedel 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.


"The book could be used for a short course for practitioners looking for solutions to particular problems, a medium course for non-computer science major who would use multiprocessor programming in their own field, or a semester-long course for computer science majors."--Reference and Research Book News, February 2013

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