The Art of Multiprocessor Programming, Revised Reprint
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Description
Revised and updated with improvements conceived in parallel programming courses, The Art of Multiprocessor Programming is an authoritative guide to multicore programming. It introduces a higher level set of software development skills than that needed for efficient single-core programming. This book provides comprehensive coverage of the new principles, algorithms, and tools necessary for effective multiprocessor programming. Students and professionals alike will benefit from thorough coverage of key multiprocessor programming issues.
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Product details
- Paperback | 536 pages
- 191 x 235 x 33.02mm | 1,070g
- 25 Jun 2012
- Elsevier Science & Technology
- Morgan Kaufmann Publishers In
- San Francisco, United States
- English
- Revised
- Revised ed.
- 0123973376
- 9780123973375
- 335,883
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
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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
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Review Text
"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
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Review quote
"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
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About Maurice Herlihy
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.
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