This Festschrift volume includes a collection of papers written in honor of the accomplishments of Professor Yonezawa on the occasion of his 65th birthday in 2012. With a few exceptions, the papers in this Festschrift were presented at an international symposium celebrating this occasion. Also included are reprints of two of Professor Yonezawa's most influential papers on the programming language ABCL. The volume is a testament strong and lasting impact Professor Yonezawa's research accomplishments as well as the inspiration he has been to colleagues and students alike.

Designing application and middleware software to run in concurrent and networked environments is a significant challenge to software developers. The patterns catalogued in this second volume of Pattern-Oriented Software Architectures (POSA) form the basis of a pattern language that addresses issues associated with concurrency and networking. The book presents 17 interrelated patterns ranging from idioms through architectural designs. They cover core elements of building concurrent and network systems: service access and configuration, event handling, synchronization, and concurrency. All patterns present extensive examples and known uses in multiple programming languages, including C++, C, and Java. The book can be used to tackle specific software development problems or read from cover to cover to provide a fundamental understanding of the best practices for constructing concurrent and networked applications and middleware. About the Authors This book has been written by the award winning team responsible for the first POSA volume "A System of Patterns", joined in this volume by Douglas C. Schmidt from University of California, Irvine (UCI), USA. Visit our Web Page

Threads are a fundamental part of the Java platform. As multicore processors become the norm, using concurrency effectively becomes essential for building high-performance applications. Java SE 5 and 6 are a huge step forward for the development of concurrent applications, with improvements to the Java Virtual Machine to support high-performance, highly scalable concurrent classes and a rich set of new concurrency building blocks. In Java Concurrency in Practice, the creators of these new facilities explain not only how they work and how to use them, but also the motivation and design patterns behind them. However, developing, testing, and debugging multithreaded programs can still be very difficult; it is all too easy to create concurrent programs that appear to work, but fail when it matters most: in production, under heavy load. Java Concurrency in Practice arms readers with both the theoretical underpinnings and concrete techniques for building reliable, scalable, maintainable concurrent applications. Rather than simply offering an inventory of concurrency APIs and mechanisms, it provides design rules, patterns, and mental models that make it easier to build concurrent programs that are both correct and performant. This book covers: Basic concepts of concurrency and thread safety Techniques for building and composing thread-safe classes Using the concurrency building blocks in java.util.concurrent Performance optimization dos and don'ts Testing concurrent programs Advanced topics such as atomic variables, nonblocking algorithms, and the Java Memory Model

Software -- Programming Languages.

If you're looking to take full advantage of multi-core processors with concurrent programming, this practical book provides the knowledge and hands-on experience you need. The Art of Concurrency is one of the few resources to focus on implementing algorithms in the shared-memory model of multi-core processors, rather than just theoretical models or distributed-memory architectures. The book provides detailed explanations and usable samples to help you transform algorithms from serial to parallel code, along with advice and analysis for avoiding mistakes that programmers typically make when first attempting these computations. Written by an Intel engineer with over two decades of parallel and concurrent programming experience, this book will help you: Understand parallelism and concurrency Explore differences between programming for shared-memory and distributed-memory Learn guidelines for designing multithreaded applications, including testing and tuning Discover how to make best use of different threading libraries, including Windows threads, POSIX threads, OpenMP, and Intel Threading Building Blocks Explore how to implement concurrent algorithms that involve sorting, searching, graphs, and other practical computations The Art of Concurrency shows you how to keep algorithms scalable to take advantage of new processors with even more cores. For developing parallel code algorithms for concurrent programming, this book is a must.

A major feature of the Ada programming language is the facilities it provides for concurrent programming. Alan Burns and Andy Wellings provide here a thorough and self-contained account of concurrent programming in Ada, and so show users, even beginners, how to harness the full power of the whole language. After giving an overview of the non-concurrent features of Ada, the authors proceed to examine in detail the uses of concurrent programming and the inherent difficulties in providing inter-process communication. The Ada tasking model is then introduced; the way it deals with these and related matters is explained in a number of separate chapters, covering system programming, real-time issues, distribution, object-oriented programming and re-use. This is the first book which deals with concurrent features in the new Ada standard, and it offers practical advice to the programmer needing to use it for embedded systems, while those interested more broadly in the development of programming languages will find many otherwise inaccessible issues probed in depth. It will thus be of value to professional software engineers and advanced students of programming alike; indeed, every Ada programmer will find it essential reading and a primary reference work. For the paperback edition the authors have made revisions throughout the text, updating and correcting where appropriate.

Offers information on how to exploit the parallel architectures in a computer's GPU to improve code performance, scalability, and resilience.