Rachid Guerraoui - Böcker

Transactional memory (TM) is an appealing paradigm for concurrent programming on shared memory architectures. With a TM, threads of an application communicate, and synchronize their actions, via in-memory transactions. Each transaction can perform any number of operations on shared data, and then either commit or abort. When the transaction commits, the effects of all its operations become immediately visible to other transactions; when it aborts, however, those effects are entirely discarded. Transactions are atomic: programmers get the illusion that every transaction executes all its operations instantaneously, at some single and unique point in time. Yet, a TM runs transactions concurrently to leverage the parallelism offered by modern processors. The aim of this book is to provide theoretical foundations for transactional memory. This includes defining a model of a TM, as well as answering precisely when a TM implementation is correct, what kind of properties it can ensure, what are the power and limitations of a TM, and what inherent trade-offs are involved in designing a TM algorithm. While the focus of this book is on the fundamental principles, its goal is to capture the common intuition behind the semantics of TMs and the properties of existing TM implementations. Table of Contents: Introduction / Shared Memory Systems / Transactional Memory: A Primer / TM Correctness Issues / Implementing a TM / Further Reading / Opacity / Proving Opacity: An Example / Opacity vs.\ Atomicity / Further Reading / The Liveness of a TM / Lock-Based TMs / Obstruction-Free TMs / General Liveness of TMs / Further Reading / Conclusions

The advent of multi-core architectures and cloud-computing has brought parallel programming into the mainstream of software development. Unfortunately, writing scalable parallel programs using traditional lock-based synchronization primitives is well known to be a hard, time consuming and error-prone task, mastered by only a minority of specialized programmers. Building on the familiar abstraction of atomic transactions, Transactional Memory (TM) promises to free programmers from the complexity of conventional synchronization schemes, simplifying the development and verification of concurrent programs, enhancing code reliability, and boosting productivity. Over the last decade TM has been subject to intense research on a broad range of aspects including hardware and operating systems support, language integration, as well as algorithms and theoretical foundations. On the industrial side, the major players of the software and hardware markets have been up-front in the research and development of prototypal products providing support for TM systems. This has recently led to the introduction of hardware TM implementations on mainstream commercial microprocessors and to the integration of TM support for the world’s leading open source compiler. In such a vast inter-disciplinary domain, the Euro-TM COST Action (IC1001) has served as a catalyzer and a bridge for the various research communities looking at disparate, yet subtly interconnected, aspects of TM. This book emerged from the idea having Euro-TM experts compile recent results in the TM area in a single and consistent volume. Contributions have been carefully selected and revised to provide a broad coverage of several fundamental issues associated with the design and implementation of TM systems, including their theoretical underpinnings and algorithmic foundations, programming language integration and verification tools, hardware supports, distributed TM systems, self-tuning mechanisms, as well as lessonslearnt from building complex TM-based applications.

DISC, the International Symposium on Distributed Computing, is an annual conference for the presentation of research on the theory, design, analysis, - plementation, and application of distributed systems and network. DISC 2004 was held on October 4-7, 2004, in Amsterdam, The Netherlands. There were 142 papers submitted to DISC this year. These were read and evaluated by the program committee members, assisted by external reviewers. The quality of submissions was high and we were unable to accept many dese- ing papers. Thirty one papers were selected at the program committee meeting in Lausanne to be included in these proceedings. The proceedings include an extended abstract of the invited talk by Ueli Maurer. In addition, they include a eulogy for Peter Ruzicka by Shmuel Zaks. The Best Student Paper Award was split and given to two papers: the paper "E?cient Adaptive Collect Using Randomization", co-authored by Hagit Attiya, FabianKuhn,MirjamWattenhoferandRogerWattenhofer,andthe paper"C- plingandSelf-stabilization",co-authoredbyLaurentFribourg,StephaneMessika and Claudine Picaronny. The support of the CWI and EPFL is gratefully acknowledged.The review process and the preparation of this volume were done using CyberChairPRO. I also thank Sebastien Baehni and Sidath Handurukande for their crucial help with these matters. August 2004 Rachid Guerraoui Peter Ruzicka 1947-2003 Peter died on Sunday, October 5, 2003, at the age of 56, after a short disease. He was a Professor of Informatics at the Faculty of Mathematics, Physics and Informatics in Comenius University, Bratislava, Slovakia. Those of us who knew himthroughDISC andother occasionsmournhisdeathandcherishhismemory.

This book constitutes the refereed proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms, Middleware 2001, held in Heidelberg, Germany, in November 2001.The 20 revised full papers presented were carefully reviewed and selected from a total of 116 submissions. The papers are organized in topical sections on Java, mobility, distributed abstractions, reliability, home and office, scalability, and quality of service.

Interest has grown rapidly over the past dozen years in the application of object-oriented programming and methods to the development of distributed, open systems. This volume presents the proceedings of a workshop intended to assess the current state of research in this field and to facilitate interaction between groups working on very different aspects of object-oriented distributed systems. The workshop was held as part of the 1993 European Conference on Object-Oriented Programming (ECOOP '93). Over fifty people submitted position papers and participated in the workshop, and almost half presented papers. The presented papers were carefully reviewed and revised after the workshop, and 14 papers were selected for this volume.

This book constitutes the refereed proceedings of the 13th European Conference on Object-Oriented Programming, ECOOP'99, held in Lisbon, Portugal in June 1999.The 20 revised full papers presented were carefully reviewed and selected from a total of 183 submissions on the basis of three to five reviews. Also included are four invited papers. The book is structured in topical sections on mixins, debugging and garbage collection, type checking, virtual and multi-methods, adaptive programming, classification and inheritance, and distributed objects.

This book constitutes the refereed proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2009, held in Lyon, France, in November 2009. The 49 revised full papers and 14 brief announcements presented together with three invited talks were carefully reviewed and selected from 126 submissions. The papers address all safety and security-related aspects of self-stabilizing systems in various areas. The most topics related to self-* systems. The special topics were alternative systems and models, autonomic computational science, cloud computing, embedded systems, fault-tolerance in distributed systems / dependability, formal methods in distributed systems, grid computing, mobility and dynamic networks, multicore computing, peer-to-peer systems, self-organizing systems, sensor networks, stabilization, and system safety and security.

Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks.

This book constitutes the revised selected papers of the First International Conference on Networked Systems, NETYS 2013, held in Marrakech, Morocco, in May 2013. The 33 papers (17 regular and 16 short papers) presented were carefully reviewed and selected from 74 submissions. They address major topics from theory and practice of networked systems: multi-core architectures, middleware, environments, storage clusters, as well as peer-to-peer, sensor, wireless, and mobile networks.

Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks.

Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure. This could, for example, result from hardware and software bugs, data poisoning or a malicious player controlling a subset of the machines. This book explains in simple terms what it means for a distributed machine learning scheme to be robust to these threats, and how to build provably robust machine learning algorithms.Studying the robustness of machine learning algorithms is a necessity given the ubiquity of these algorithms in both the private and public sectors. Accordingly, over the past few years, we have witnessed a rapid growth in the number of articles published on the robustness of distributed machine learning algorithms. We believe it is time to provide a clear foundation to this emerging and dynamic field. By gathering the existing knowledge and democratizing the concept of robustness, the book provides the basis for a new generation of reliable and safe machine learning schemes. In addition to introducing the problem of robustness in modern machine learning algorithms, the book will equip readers with essential skills for designing distributed learning algorithms with enhanced robustness. Moreover, the book provides a foundation for future research in this area.