This book includes the papers presented at the Third International Workshop on Distributed Algorithms organized at La Colle-sur-Loup, near Nice, France, September 26-28, 1989 which followed the first two successful international workshops in Ottawa (1985) and Amsterdam (1987). This workshop provided a forum for researchers and others interested in distributed algorithms on communication networks, graphs, and decentralized systems. The aim was to present recent research results, explore directions for future research, and identify common fundamental techniques that serve as building blocks in many distributed algorithms. Papers describe original results in all areas of distributed algorithms and their applications, including: distributed combinatorial algorithms, distributed graph algorithms, distributed algorithms for control and communication, distributed database techniques, distributed algorithms for decentralized systems, fail-safe and fault-tolerant distributed algorithms, distributed optimization algorithms, routing algorithms, design of network protocols, algorithms for transaction management, composition of distributed algorithms, and analysis of distributed algorithms.

Each week of this three week meeting was a self-contained event, although each had the same underlying theme - the effect of parallel processing on numerical analysis. Each week provided the opportunity for intensive study to broaden participants' research interests or deepen their understanding of topics of which they already had some knowledge. There was also the opportunity for continuing individual research in the stimulating environment created by the presence of several experts of international stature. This volume contains lecture notes for most of the major courses of lectures presented at the meeting; they cover topics in parallel algorithms for large sparse linear systems and optimization, an introductory survey of level-index arithmetic and superconvergence in the finite element method.

This volume presents the proceedings of a workshop at which major Parallel Lisp activities in the US and Japan were explained. Work covered includes Multilisp and Mul-T at MIT, Qlisp at Stanford, Lucid and Parcel at Illinois, PaiLisp at Tohoku University, Multiprocessor Lisp on TOP-1 at IBM Tokyo Research, and concurrent programming in TAO. Most papers present languages and systems of Parallel Lisp and are in particular concerned with: - Language constructs of Parallel Lisp and their meanings from the standpoint of implementing Parallel Lisp systems; - Some important technical issues such as parallel garbage collection, dynamic task partitioning, futures and continuations in parallelism, automatic parallelization of Lisp programs, and the kernel concept of Parallel Lisp. Some performance results are reported that suggest practical applicability of Parallel Lisp systems in the near future. Several papers on concurrent object-oriented systems are also included.

This work relates different approaches for the modelling of parallel processes. On the one hand there are the so-called "process algebras" or "abstract programming languages" with Milner's Calculus of Communicating Systems (CCS) and the theoretical version of Hoare's Communicating Sequential Processes (CSP) as main representatives. On the other hand there are machine models, i.e. the classical finite state automata (transition systems), for which, however, more discriminating notions of equivalence than equality of languages are used; and secondly, there are differently powerful types of Petri nets, namely safe and general (place/transition) nets respectively, and predicate/transition nets. Within a uniform framework the syntax and the operational semantics of CCS and TCSP are explained. We consider both, Milner's well-known interleaving semantics, which is based on infinite transition systems, as well as the new distributed semantics introduced by Degano et al., which is based on infinite safe nets. The main part of this work contains three syntax-driven constructions of transition systems, safe nets, and predicate/transition nets respectively. Each of them is accompanied by a proof of consistency. Due to intrinsic limits, which are also investigated here, neither for transition systems and finite nets, nor for general nets does a finite consistent representation of all CCS and TCSP programs exist. However sublanguages which allow finite representations are discerned. On the other hand the construction of predicate/transition nets is possible for all CCS programs in which every choice and every recursive body starts sequentially.

It was the aim of the conference to present issues in parallel computing to a community of potential engineering/scientific users. An overview of the state-of-the-art in several important research areas is given by leading scientists in their field. The classification question is taken up at various points, ranging from parametric characterizations, communication structure, and memory distribution to control and execution schemes. Central issues in multiprocessing hardware and operation, such as scalability, techniques of overcoming memory latency and synchronization overhead, as well as fault tolerance of communication networks are discussed. The problem of designing and debugging parallel programs in a user-friendly environment is addressed and a number of program transformations for enhancing vectorization and parallelization in a variety of program situations are described. Two different algorithmic techniques for the solution of certain classes of partial differential equations are discussed. The properties of domain-decomposition algorithms and their mapping onto a CRAY-XMP-type architecture are investigated and an overview is given of the merit of various approaches to exploiting the acceleration potential of multigrid methods. Finally, an abstract performance modeling technique for the behavior of applications on parallel and vector architectures is described.

The papers collected in this volume are most of the material presented at the Advanced School on Mathematical Models for the Semantics of Parallelism, held in Rome, September 24- October 1, 1986. The need for a comprehensive and clear presentation of the several semantical approaches to parallelism motivated the stress on mathematical models, by means of which comparisons among different approaches can also be performed in a perspicuous way.

"WOPPLOT 86 - Workshop on Parallel Processing: Logic, " "Organization and Technology" - gathered together experts from various fields for a broad overview of current trends in parallel processing. There are contributions from logic (e.g., the connection between time and logic, or non-monotonic reasoning); from organizational structure theory (of great importance for pyramid architecture) and structure representation; from intrinsic parallelism and problem classification; from developments in future technologies (3-D Silicon technology, molecular electronics); and from various applications (pattern storage in adaptive memories, simulation of physical systems). The proceedings show clearly that progress in parallel processing is an interdisciplinary goal; they present a cross section of the state of the art as well as of future trends. Furthermore, some contributions (in particular, those from logic and organization) deserve a broader interest also outside the field of parallel processing.

Build your expertise in the BPF virtual machine in the Linux kernel with this practical guide for systems engineers. You'll not only dive into the BPF program lifecycle but also learn to write applications that observe and modify the kernel's behavior; inject code to monitor, trace, and securely observe events in the kernel; and more. Authors David Calavera and Lorenzo Fontana help you harness the power of BPF to make any computing system more observable. Familiarize yourself with the essential concepts you'll use on a day-to-day basis and augment your knowledge about performance optimization, networking, and security. Then see how it all comes together with code examples in C, Go, and Python. Write applications that use BPF to observe and modify the Linux kernel's behavior on demand Inject code to monitor, trace, and observe events in the kernel in a secure way-no need to recompile the kernel or reboot the system Explore code examples in C, Go, and Python Gain a more thorough understanding of the BPF program lifecycle

This is the book for Gophers who want to learn how to build distributed systems. You know the basics of Go and are eager to put your knowledge to work. Build distributed services that are highly available, resilient, and scalable. This book is just what you need to apply Go to real-world situations. Level up your engineering skills today. Take your Go skills to the next level by learning how to design, develop, and deploy a distributed service. Start from the bare essentials of storage handling, then work your way through networking a client and server, and finally to distributing server instances, deployment, and testing. All this will make coding in your day job or side projects easier, faster, and more fun. Create your own distributed services and contribute to open source projects. Build networked, secure clients and servers with gRPC. Gain insights into your systems and debug issues with observable services instrumented with metrics, logs, and traces. Operate your own Certificate Authority to authenticate internal web services with TLS. Automatically handle when nodes are added or removed to your cluster with service discovery. Coordinate distributed systems with replicated state machines powered by the Raft consensus algorithm. Lay out your applications and libraries to be modular and easy to maintain. Write CLIs to configure and run your applications. Run your distributed system locally and deploy to the cloud with Kubernetes. Test and benchmark your applications to ensure they're correct and fast. Dive into writing Go and join the hundreds of thousands who are using it to build software for the real world. What You Need: Go 1.13+ and Kubernetes 1.16+

In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs

This book is an introduction to the field of parallel algorithms and the underpinning techniques to realize the parallelization. The emphasis is on designing algorithms within the timeless and abstracted context of a high-level programming language. The focus of the presentation is on practical applications of the algorithm design using different models of parallel computation. Each model is illustrated by providing an adequate number of algorithms to solve some problems that quite often arise in many applications in science and engineering.The book is largely self-contained, presuming no special knowledge of parallel computers or particular mathematics. In addition, the solutions to all exercises are included at the end of each chapter.The book is intended as a text in the field of the design and analysis of parallel algorithms. It includes adequate material for a course in parallel algorithms at both undergraduate and graduate levels.

The programming language Fortran dates back to 1957 when a team of IBM engineers released the first Fortran Compiler. During the past 60 years, the language had been revised and updated several times to incorporate more features to enable writing clean and structured computer programs. The present version is Fortran 2018. Since the dawn of the computer era, there had been a constant demand for a "larger" and "faster" machine. To increase the speed there are three hurdles. The density of the active components on a VLSI chip cannot be increased indefinitely and with the increase of the density heat dissipation becomes a major problem. Finally, the speed of any signal cannot exceed the velocity of the light. However, by using several inexpensive processors in parallel coupled with specialized software and hardware, programmers can achieve computing speed similar to a supercomputer. This book can be used to learn the modern Fortran from the beginning and the technique of developing parallel programs using Fortran. It is for anyone who wants to learn Fortran. Knowledge beyond high school mathematics is not required. There is not another book on the market yet which deals with Fortran 2018 as well as parallel programming. FEATURES Descriptions of majority of Fortran 2018 instructions Numerical Model String with Variable Length IEEE Arithmetic and Exceptions Dynamic Memory Management Pointers Bit handling C-Fortran Interoperability Object Oriented Programming Parallel Programming using Coarray Parallel Programming using OpenMP Parallel Programming using Message Passing Interface (MPI) THE AUTHOR Dr Subrata Ray, is a retired Professor, Indian Association for the Cultivation of Science, Kolkata.

Take advantage of Kotlin's concurrency primitives to write efficient multithreaded applications Key Features Learn Kotlin's unique approach to multithreading Work through practical examples that will help you write concurrent non-blocking code Improve the overall execution speed in multiprocessor and multicore systems Book DescriptionThe primary requirements of modern-day applications are scalability, speed, and making the most use of hardware. Kotlin meets these requirements with its immense support for concurrency. Many concurrent primitives of Kotlin, such as channels and suspending functions, are designed to be non-blocking and efficient. This allows for new approaches to concurrency and creates unique challenges for the design and implementation of concurrent code. Learning Concurrency in Kotlin addresses those challenges with real-life examples and exercises that take advantage of Kotlin's primitives. Beginning with an introduction to Kotlin's coroutines, you will learn how to write concurrent code and understand the fundamental concepts needed to be able to write multithreaded software in Kotlin. You'll explore how to communicate between and synchronize your threads and coroutines to write asynchronous applications that are collaborative. You'll also learn how to handle errors and exceptions, as well as how to leverage multi-core processing. In addition to this, you'll delve into how coroutines work internally, allowing you to see the bigger picture. Throughout the book you'll build an Android application - an RSS reader - designed and implemented according to the different topics covered in the book What you will learn Understand Kotlin's approach to concurrency Implement sequential and asynchronous suspending functions Create suspending data sources that are resumed on demand Explore the best practices for error handling Use channels to communicate between coroutines Uncover how coroutines work under the hood Who this book is forIf you're a Kotlin or Android developer interested in learning how to program concurrently to enhance the performance of your applications, this is the book for you.

Almost all software solutions are developed through academic research and implemented only in prototype machines leaving the field of software techniques for maintaining the cache coherence widely open for future research and development. This book is a collection of all the representative approaches to software coherence maintenance including a number of related efforts in the performance evaluation field.
The book presents a selection of 27 papers dealing with state-of-the-art software solutions for cache coherence maintenance in shared-memory multiprocessors. It begins with a set of four introductory readings that provides a brief overview of the cache coherence problem and introduces software solutions to the problem. The text defines and illustrates static and dynamic software schemes, techniques for modeling performance evaluation mechanisms, and performance evaluation studies.
The book is intended for the experienced reader in computer engineering but possibly a novice in the topic of cache coherence. It also provides an in-depth understanding of the problem as well as a comprehensive overview for multicomputer designers, computer architects, and compiler writers. In addition, it is a software coherence reference handbook for advanced undergraduate and typical graduate students in multiprocessing and multiprogramming areas.

This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2022, held as a virtual event in June 2022 (due to the Covid-19 pandemic).The 12 revised full papers presented were carefully reviewed and selected from 19 submissions. In addition to this,1 keynote paper was included in the workshop. The volume contains two sections: Technical papers and Open Scheduling Problems.

Ever since the invention of the computer, users have demanded more and more computational power to tackle increasingly complex problems. A common means of increasing the amount of computational power available for solving a problem is to use parallel computing. Unfortunately, however, creating efficient parallel programs is notoriously difficult. In addition to all of the well-known problems that are associated with constructing a good serial algorithm, there are a number of problems specifically associated with constructing a good parallel algorithm. These mainly revolve around ensuring that all processors are kept busy and that they have timely access to the data that they require. Unfortunately, however, controlling a number of processors operating in parallel can be exponentially more complicated than controlling one processor. Furthermore, unlike data placement in serial programs, where sophisticated compilation techniques that optimise cache behaviour and memory interleaving are common, optimising data placement throughout the vastly more complex memory hierarchy present in parallel computers is often left to the parallel application programmer. All of these problems are compounded by the large number of parallel computing architectures that exist, because they often exhibit vastly different performance characteristics, which makes writing well-optimised, portable code especially difficult. The primary weapon against these problems in a parallel programmer's or parallel computer architect's arsenal is -- or at least should be -- the art of performance prediction. This book provides a historical exposition of over four decades of research into techniques for modelling the performance of computer programs running on parallel computers.

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment of theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, and essential notions of scheduling. The book extracts fundamental ideas and algorithmic principles from the mass of parallel algorithm expertise and practical implementations developed over the last few decades.

In the first section of the text, the authors cover two classical theoretical models of parallel computation (PRAMs and sorting networks), describe network models for topology and performance, and define several classical communication primitives. The next part deals with parallel algorithms on ring and grid logical topologies as well as the issue of load balancing on heterogeneous computing platforms. The final section presents basic results and approaches for common scheduling problems that arise when developing parallel algorithms. It also discusses advanced scheduling topics, such as divisible load scheduling and steady-state scheduling.

With numerous examples and exercises in each chapter, this text encompasses both the theoretical foundations of parallel algorithms and practical parallel algorithm design.

Microservices can have a positive impact on your enterprise-just ask Amazon and Netflix-but you can fall into many traps if you don't approach them in the right way. This practical guide covers the entire microservices landscape, including the principles, technologies, and methodologies of this unique, modular style of system building. You'll learn about the experiences of organizations around the globe that have successfully adopted microservices. In three parts, this book explains how these services work and what it means to build an application the Microservices Way. You'll explore a design-based approach to microservice architecture with guidance for implementing various elements. And you'll get a set of recipes and practices for meeting practical, organizational, and cultural challenges to microservice adoption. Learn how microservices can help you drive business objectives Examine the principles, practices, and culture that define microservice architectures Explore a model for creating complex systems and a design process for building a microservice architecture Learn the fundamental design concepts for individual microservices Delve into the operational elements of a microservices architecture, including containers and service discovery Discover how to handle the challenges of introducing microservice architecture in your organization

The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows: Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.

The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows: Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.