Foundations of Multithreaded, Parallel, and Distributed Programming

Autorentext
Gregory Andrews received a B.S. degree in Mathematics from Stanford University in 1969 and a Ph.D. degree in Computer Science from the University of Washington in 1974. From 1974-79 he was an Assistant Professor at Cornell University. Since 1979 he has been at The University of Arizona, where he is currently Professor of Computer Science. From 1986-93 he chaired the department; in 1986 he received a distinguished teaching award. Greg has been on the editorial board of Information Processing Letters since 1979. He was the general chair of the Twelfth ACM Symposium on Operating Systems Principles in 1989 and has been on the program committees of numerous conferences. From 1988-92 he was on advisory committees for the computing directorate of the National Science Foundation. Since 1991 he has been on the Board of Directors of the Computing Research Association (CRA). Greg's research interests include all aspects of concurrent programming. A long-term project has been the design and implementation of the SR programming language. Current work focuses on the development of Filaments, a software package that provides efficient fine-grain parallelism on a variety of parallel machines.

0201357526AB04062001

Klappentext
Foundations of Multithreaded, Parallel, and Distributed Programming covers, and then applies, the core concepts and techniques needed for an introductory course in this subject. Its emphasis is on the practice and application of parallel systems, using real-world examples throughout.Greg Andrews teaches the fundamental concepts of multithreaded, parallel and distributed computing and relates them to the implementation and performance processes. He presents the appropriate breadth of topics and supports these discussions with an emphasis on performance.Features Emphasizes how to solve problems, with correctness the primary concern and performance an important, but secondary, concern Includes a number of case studies which cover such topics as pthreads, MPI, and OpenMP libraries, as well as programming languages like Java, Ada, high performance Fortran, Linda, Occam, and SR Provides examples using Java syntax and discusses how Java deals with monitors, sockets, and remote method invocation Covers current programming techniques such as semaphores, locks, barriers, monitors, message passing, and remote invocation Concrete examples are executed with complete programs, both shared and distributed Sample applications include scientific computing and distributed systems

0201357526B04062001

Zusammenfassung
Foundations of Multithreaded, Parallel, and Distributed Programming covers, and then applies, the core concepts and techniques needed for an introductory course in this subject. Its emphasis is on the practice and application of parallel systems, using real-world examples throughout.Greg Andrews teaches the fundamental concepts of multithreaded, parallel and distributed computing and relates them to the implementation and performance processes. He presents the appropriate breadth of topics and supports these discussions with an emphasis on performance.

Inhalt


1. The Concurrent Computing Landscape.
The Essence of Concurrent Programming.Hardware Architectures.Single Processor Machines.Shared-Memory Multiprocessors.Multicomputers Networks.Applications and Programming Styles.Iterative Parallelism: Matrix Multiplication.Recursive Parallelism: Adaptive Quadrature.Producers and Consumers: Unix Pipes.Clients and Servers: Remote Files.Peers: Distributed Matrix Multiplication.Summary of Programming Notation.Declarations Sequential Statements.Concurrent Statements and Process Declarations.Comments.I. SHARED VARIABLE PROGRAMMING. 2. Processes and Synchronization.
States, Actions, Histories, and Properties.Parallelization: Finding Patterns in Files.Synchronization: The Maximum of an Array.Atomic Actions and Await Statements.Fine-Grained Atomicity.Specifying Synchronization: The Await Statement.Finding Patterns in a File Revisited.A Synopsis of Axiomatic Semantics.Formal Logical Systems.A Programming Logic.Semantics of Concurrent Execution.Techniques for Avoiding Interference.Disjoint Variables Weakened Assertions.Global Invariants.Synchronization.An Example: The Array Copy Problem Revisited.Safety and Liveness Properties.Proving Safety Properties.Scheduling Policies and Fairness.3. Locks and Barriers.
The Critical Section Problem.Critical Sections: Spin Locks.Test and Set.Test and Test and Set.Implementing Await Statements.Critical Sections: Fair Solutions.The Tie-Breaker Algorithm.The Ticket Algorithm.The Bakery Algorithm.Barrier Synchronization.Shared Counter.Flags and Coordinators.Symmetric Barriers.Data Parallel Algorithms.Parallel Prefix Computations.Operations on Linked Lists.Grid Computations: Laplace's Equation.Synchronous Multiprocessors.Parallel Computing with a Bag of Tasks.Matrix Multiplication.Adaptive Quadrature.4. Semaphores.
Syntax and Semantics.Basic Problems and Techniques.Critical Sections: Mutual Exclusion.Barriers: Signaling Events.Producers and Consumers: Split Binary Semaphores.Bounded Buffers: Resource Counting.The Dining Philosophers.Readers and Writers.Readers/Writers as an Exclusion Problem.Readers/Writers Using Condition Synchronization.The Technique of Passing the Baton.Alternative Scheduling Policies.Resource Allocation and Scheduling.Problem Definition and General Solution Pattern.Shortest-Job-Next Allocation.Case Study: Pthreads.Thread Creation.Semaphores.Example: A Simple Producer and Consumer.5. Monitors.
Syntax and Semantics.Mutual Exclusion.Condition Variables.Signaling Disciplines.Additional Operations on Condition Variables.Synchronization Techniques.Bounded Buffers: Basic Condition Synchronization.Readers and Writers: Broadcast Signal.Shortest-Job-Next Allocation: Priority Wait.Interval Timer: Covering Conditions.The Sleeping Barber: Rendezvous.Disk Scheduling: Program Structures.Scheduler as a Separate Monitor.Scheduler as an Intermediary.Scheduler as a Nested Monitor.Case Study: Java.The Threads Class.Synchronized Methods.Parallel Readers/Writers.Exclusive Readers/Writers.True Readers/Writers.Case Study: Pthreads.Locks and Condition Variables.Example: Summing the Elements of a Matrix.6. Implementations.
A Single-Processor Kernel.…

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