The Art of Multiprocessor Programming, Revised Reprint - 1st Edition - ISBN: 9780123973375, 9780123977953

The Art of Multiprocessor Programming, Revised Reprint

1st Edition

Authors: Maurice Herlihy Nir Shavit
eBook ISBN: 9780123977953
Paperback ISBN: 9780123973375
Imprint: Morgan Kaufmann
Published Date: 22nd May 2012
Page Count: 536
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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.

Key Features

  • This revised edition incorporates much-demanded updates throughout the book, based on feedback and corrections reported from classrooms since 2008
  • Learn the fundamentals of programming multiple threads accessing shared memory
  • Explore mainstream concurrent data structures and the key elements of their design, as well as synchronization techniques from simple locks to transactional memory systems
  • Visit the companion site and download source code, example Java programs, and materials to support and enhance the learning experience


Students in multiprocessor and multicore programming courses and engineers working with multiprocessor and multicore systems.

Table of Contents



Product Note


Suggested Ways to Teach the Art of Multiprocessor Programming

1. Introduction

1.1 Shared Objects and Synchronization

1.2 A Fable

1.3 The Producer–Consumer Problem

1.4 The Readers–Writers Problem

1.5 The Harsh Realities of Parallelization

1.6 Parallel Programming

1.7 Chapter Notes

I Principles

2. Mutual Exclusion

2.1 Time

2.2 Critical Sections

2.3 2-Thread Solutions

2.4 The Filter Lock

2.5 Fairness

2.6 Lamport’s Bakery Algorithm

2.7 Bounded Timestamps

2.8 Lower Bounds on the Number of Locations

2.9 Chapter Notes

3. Concurrent Objects

3.1 Concurrency and Correctness

3.2 Sequential Objects

3.3 Quiescent Consistency

3.4 Sequential Consistency

3.5 Linearizability

3.6 Formal Definitions

3.7 Progress Conditions

3.8 The Java Memory Model

3.9 Remarks

3.10 Chapter Notes

4. Foundations of Shared Memory

4.1 The Space of Registers

4.2 Register Constructions

4.3 Atomic Snapshots

4.4 Chapter Notes

5. The Relative Power of Primitive Synchronization Operations

5.1 Consensus Numbers

5.2 Atomic Registers

5.3 Consensus Protocols

5.4 FIFO Queues

5.5 Multiple Assignment Objects

5.6 Read–Modify–Write Operations

5.7 Common2 RMW Operations

5.8 The compareAndSet() Operation

5.9 Chapter Notes

6. Universality of Consensus

6.1 Introduction

6.2 Universality

6.3 A Lock-Free Universal Construction

6.4 A Wait-Free Universal Construction

6.5 Chapter Notes

II Practice

7. Spin Locks and Contention

7.1 Welcome to the Real World

7.2 Test-And-Set Locks

7.3 TAS-Based Spin Locks Revisited

7.4 Exponential Backoff

7.5 Queue Locks

7.6 A Queue Lock with Timeouts

7.7 A Composite Lock

7.8 Hierarchical Locks

7.9 One Lock To Rule Them All

7.10 Chapter Notes

8. Monitors and Blocking Synchronization

8.1 Introduction

8.2 Monitor Locks and Conditions

8.3 Readers–Writers Locks

8.4 Our Own Reentrant Lock

8.5 Semaphores

8.6 Chapter Notes

9. Linked Lists

9.1 Introduction

9.2 List-Based Sets

9.3 Concurrent Reasoning

9.4 Coarse-Grained Synchronization

9.5 Fine-Grained Synchronization

9.6 Optimistic Synchronization

9.7 Lazy Synchronization

9.8 Non-Blocking Synchronization

9.9 Discussion

9.10 Chapter Notes

10. Concurrent Queues and the ABA Problem

10.1 Introduction

10.2 Queues

10.3 A Bounded Partial Queue

10.4 An Unbounded Total Queue

10.5 An Unbounded Lock-Free Queue

10.6 Memory Reclamation and the ABA Problem

10.7 Dual Data Structures

10.8 Chapter Notes

11. Concurrent Stacks and Elimination

11.1 Introduction

11.2 An Unbounded Lock-Free Stack

11.3 Elimination

11.4 The Elimination Backoff Stack

11.5 Chapter Notes

12. Counting, Sorting, and Distributed Coordination

12.1 Introduction

12.2 Shared Counting

12.3 Software Combining

12.4 Quiescently Consistent Pools and Counters

12.5 Counting Networks

12.6 Diffracting Trees

12.7 Parallel Sorting

12.8 Sorting Networks

12.9 Sample Sorting

12.10 Distributed Coordination

12.11 Chapter Notes

13. Concurrent Hashing and Natural Parallelism

13.1 Introduction

13.2 Closed-Address Hash Sets

13.3 A Lock-Free Hash Set

13.4 An Open-Addressed Hash Set

13.5 Chapter Notes

14. Skiplists and Balanced Search

14.1 Introduction

14.2 Sequential Skiplists

14.3 A Lock-Based Concurrent Skiplist

14.4 A Lock-Free Concurrent Skiplist

14.5 Concurrent Skiplists

14.6 Chapter Notes

15. Priority Queues

15.1 Introduction

15.2 An Array-Based Bounded Priority Queue

15.3 A Tree-Based Bounded Priority Queue

15.4 An Unbounded Heap-Based Priority Queue

15.5 A Skiplist-Based Unbounded Priority Queue

15.6 Chapter Notes

16. Futures, Scheduling, and Work Distribution

16.1 Introduction

16.2 Analyzing Parallelism

16.3 Realistic Multiprocessor Scheduling

16.4 Work Distribution

16.5 Work-Stealing Dequeues

16.6 Chapter Notes

17. Barriers

17.1 Introduction

17.2 Barrier Implementations

17.3 Sense-Reversing Barrier

17.4 Combining Tree Barrier

17.5 Static Tree Barrier

17.6 Termination Detecting Barriers

17.7 Chapter Notes

18. Transactional Memory

18.1 Introduction

18.2 Transactions and Atomicity

18.3 Software Transactional Memory

18.4 Hardware Transactional Memory

18.5 Chapter Notes

III Appendix

A. Software Basics

B. Hardware Basics



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About the Author

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. Maurice 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, the highest award in theoretical computer science. In 2012 he shared the Edsger W. Dijkstra Prize In Distributed Computing with Nir Shavit.

Affiliations and Expertise

Brown University, Providence, RI, USA

Nir Shavit

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, the highest award in theoretical computer science. 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. In 2012 he shared the Edsger W. Dijkstra Prize In Distributed Computing with Maurice Herlihy.

Affiliations and Expertise

Professor of Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA


"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