Over 25 hands-on recipes to create robust and highly-efficient cross-platform distributed applications with the Boost.Asio library About This Book * Build highly efficient distributed applications with ease * Enhance your cross-platform network programming skills with one of the most reputable C++ libraries * Find solutions to real-world problems related to network programming with ready-to-use recipes using this detailed and practical handbook Who This Book Is For If you want to enhance your C++ network programming skills using the Boost.Asio library and understand the theory behind development of distributed applications, this book is just what you need. The prerequisite for this book is experience with general C++11. To get the most from the book and comprehend advanced topics, you will need some background experience in multithreading. What You Will Learn * Boost your working knowledge of one of the most reputable C++ networking libraries-Boost.Asio * Familiarize yourself with the basics of TCP and UDP protocols * Create scalable and highly-efficient client and server applications * Understand the theory behind development of distributed applications * Increase the security of your distributed applications by adding SSL support * Implement a HTTP client easily * Use iostreams, scatter-gather buffers, and timers In Detail Starting with recipes demonstrating the execution of basic Boost.Asio operations, the book goes on to provide ready-to-use implementations of client and server applications from simple synchronous ones to powerful multithreaded scalable solutions. Finally, you are presented with advanced topics such as implementing a chat application, implementing an HTTP client, and adding SSL support. All the samples presented in the book are ready to be used in real projects just out of the box. As well as excellent practical examples, the book also includes extended supportive theoretical material on distributed application design and construction. Style and approach This book is a set of recipes, each containing the statement and description of a particular practical problem followed by code sample providing the solution to the problem and detailed step-by-step explanation. Recipes are grouped by topic into chapters and ordered by the level of complexity from basic to advanced.

Create robust and scalable applications along with responsive UI using concurrency and the multi-threading infrastructure in .NET and C# About This Book * Learn to combine your asynchronous operations with Task Parallel Library * Master C#'s asynchronous infrastructure and use asynchronous APIs effectively to achieve optimal responsiveness of the application * An easy-to-follow, example-based guide that helps you to build scalable applications using concurrency in C# Who This Book Is For If you are a C# developer who wants to develop modern applications in C# and wants to overcome problems by using asynchronous APIs and standard patterns, then this book is ideal for you. Reasonable development knowledge, an understanding of core elements and applications related to the .Net platform, and also the fundamentals of concurrency is assumed. What You Will Learn * Apply general multithreading concepts to your application's design * Leverage lock-free concurrency and learn about its pros and cons to achieve efficient synchronization between user threads * Combine your asynchronous operations with Task Parallel Library * Make your code easier with C#'s asynchrony support * Use common concurrent collections and programming patterns * Write scalable and robust server-side asynchronous code * Create fast and responsible client applications * Avoid common problems and troubleshoot your multi-threaded and asynchronous applications In Detail Starting with the traditional approach to concurrency, you will learn how to write multithreaded concurrent programs and compose ways that won't require locking. You will explore the concepts of parallelism granularity, and fine-grained and coarse-grained parallel tasks by choosing a concurrent program structure and parallelizing the workload optimally. You will also learn how to use task parallel library, cancellations, timeouts, and how to handle errors. You will know how to choose the appropriate data structure for a specific parallel algorithm to achieve scalability and performance. Further, you'll learn about server scalability, asynchronous I/O, and thread pools, and write responsive traditional Windows and Windows Store applications. By the end of the book, you will be able to diagnose and resolve typical problems that could happen in multithreaded applications. Style and approach An easy-to-follow, example-based guide that will walk you through the core principles of concurrency and multithreading using C#.

Get to grips with the advanced concepts of interactive computing to make the most out of IPython About This Book * Most updated book on Interactive computing with IPython 4.0; * Detailed, example-rich guide that lets you use the most advanced level interactive programming with IPython; * Get flexible interactive programming with IPython using this comprehensive guide Who This Book Is For This book is for IPython developers who want to make the most of IPython and perform advanced scientific computing with IPython utilizing the ease of interactive computing. It is ideal for users who wish to learn about the interactive and parallel computing properties of IPython 4.0, along with its integration with third-party tools and concepts such as testing and documenting results. What You Will Learn * Develop skills to use IPython for high performance computing (HPC) * Understand the IPython interactive shell * Use XeroMQ and MPI to pass messages * Integrate third-party tools like R, Julia, and JavaScript with IPython * Visualize the data * Acquire knowledge to test and document the data * Get to grips with the recent developments in the Jupyter notebook system In Detail IPython is an interactive computational environment in which you can combine code execution, rich text, mathematics, plots, and rich media. This book will get IPython developers up to date with the latest advancements in IPython and dive deep into interactive computing with IPython. This an advanced guide on interactive and parallel computing with IPython will explore advanced visualizations and high-performance computing with IPython in detail. You will quickly brush up your knowledge of IPython kernels and wrapper kernels, then we'll move to advanced concepts such as testing, Sphinx, JS events, interactive work, and the ZMQ cluster. The book will cover topics such as IPython Console Lexer, advanced configuration, and third-party tools. By the end of this book, you will be able to use IPython for interactive and parallel computing in a high-performance computing environment. Style and approach This is a comprehensive guide to IPython for interactive, exploratory and parallel computing. It will let the IPython get up to date with the latest advancements in IPython and dive deeper into interactive computing with IPython

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The new edition of a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to understand algorithms intuitively and from different perspectives. Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included. The algorithms presented in the book are for the most part "classics," selected because they shed light on the algorithmic design of distributed systems or on key issues in distributed computing and concurrent programming. This second edition has been substantially revised. A new chapter on distributed transaction offers up-to-date treatment of database transactions and the important evolving area of transactional memory. A new chapter on security discusses two exciting new topics: blockchains and quantum cryptography. Sections have been added that cover such subjects as rollback recovery, fault-tolerant termination detection, and consensus for shared memory. An appendix offers pseudocode descriptions of many algorithms. Solutions and slides are available for instructors. Distributed Algorithms can be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field.

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A guide to advanced features of MPI, reflecting the latest version of the MPI standard, that takes an example-driven, tutorial approach. This book offers a practical guide to the advanced features of the MPI (Message-Passing Interface) standard library for writing programs for parallel computers. It covers new features added in MPI-3, the latest version of the MPI standard, and updates from MPI-2. Like its companion volume, Using MPI, the book takes an informal, example-driven, tutorial approach. The material in each chapter is organized according to the complexity of the programs used as examples, starting with the simplest example and moving to more complex ones. Using Advanced MPI covers major changes in MPI-3, including changes to remote memory access and one-sided communication that simplify semantics and enable better performance on modern hardware; new features such as nonblocking and neighborhood collectives for greater scalability on large systems; and minor updates to parallel I/O and dynamic processes. It also covers support for hybrid shared-memory/message-passing programming; MPI_Message, which aids in certain types of multithreaded programming; features that handle very large data; an interface that allows the programmer and the developer to access performance data; and a new binding of MPI to Fortran.

According to many social thinkers it is not possible to quantify the performance of organizations on the basis of the values produced. One initial reply to this critique is that the axiological approach in systems theory aims to fulfil a dual function. On one side, it takes a whole set of universal reference values into consideration which in the end spur human motivation and action justifying life in society, among them the own survival of Homo sapiens which could be in danger today, On the other side, this book proposes to measure this axiological efficiency in operational statistical terms and consequently looking for verifiable results. Therefore, the first aim of this book is to present, define and measure a new concept of "organisational efficiency" which is not limited to known economic aspects or related to neoliberal premises or other ideological misconceptions. On the contrary, for the authors organisational efficiency must address the entire system of values, projected or attained. Duly substantiated criticism can and must be levelled only against any society's or organisation's system of values. More specifically, the texts hereunder the seven works in this book constitute a preliminary attempt to set up an operational quantitative methodology for that purpose. The second aim is to introduce different approaches to measure efficiency applied to specific problems within organisations. On the whole, all the articles identify a number of ways of addressing organisational efficiency, providing a better understanding and critique of this concept.

IBM Cognos BI v10.2 is an advanced suite of business intelligence tools that empower a business with a wide range of capabilities to plan, design, develop, manage reports, analysis, and design dashboards to deliver effective business intelligence strategies. This book particularly focuses on understanding the administration aspects of managing a Cognos BI environment. This fast-paced guide will provide you with practical hands-on experience of all the necessary features to administer an IBM Cognos environment.

Written as a step-by-step guide, Getting Started with Hazelcast will teach you all you need to know to make your application data scalable. This book is a great introduction for Java developers, software architects, or developers looking to enable scalable and agile data within their applications. You should have programming knowledge of Java and a general familiarity with concepts like data caching and clustering.

In quantum computing, and because all of the states of the quantum system can exist simultaneously, all of the paths of the quantum computations tree from the root to the leaves occur in parallel and only after measurement a single path will be observed as the whole system's composite state will collapse into that single path. From a computation perspective, each path in the tree of quantum computing is a single processing, and thus a massive computational parallelism exists with massive number of calculations performed simultaneously. Systolic devices provide inexpensive but massive calculation power, and are cost-effective, high-performance, and special-purpose systems that have wide range of implementations such as in solving several regular and compute-bound problems containing repetitive multiple operations on large arrays of data. This book presents research in the study of parallel computing.

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.

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you'll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA's parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA's shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations

Communicating Process Architecture (CPA) describes an approach to system development that is process-oriented. It makes no great distinction between hardware and software. It has a major root in the theory of Communicating Sequential Processes (CSP). However, the underlying theory is not limited to CSP. The importance of mobility of both channel and process within a network sees integration with ideas from the eth-calculus. Other formalisms are also exploited, such as BSP and MPI. The focus is on sound methods for the engineering of significant concurrent systems, including those that are distributed (across the Internet or within a single chip) and/or software-scheduled on a single execution unit. Traditionally, at CPA, the emphasis has been on theory and practice - developing and applying tools based upon CSP and related theories to build high-integrity systems of significant size. In particular, interest focuses on achieving scalability and security against error. The development of Java, C, and C++, libraries to facilitate secure concurrent programming using 'mainstream' languages has allowed CPA to continue and proliferate. This work continues in support of the engineering of distributed applications. Recently, there has been greater reference to theory and its more direct application to programming systems and languages. In this volume the formal CSP is very well presented. The papers provide a healthy mixture of the academic and commercial, software and hardware, application and infrastructure, which reflects the nature of the discipline.

Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are routinely ported to platforms ranging from PCs to mainframes, most parallel programs only ever run on one type of machine. One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run. Those that have been platform-independent have usually also had poor performance.Many researchers now believe that object-oriented languages may offer a solution. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming.Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism.For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself. By comparing the implementations of the polygon overlay problem in each system, the reader can get a better sense of their expressiveness and functionality for a common problem. For the systems community, the chapters contain a discussion of the implementation of the various compilers and runtime systems. In addition to discussing the performance of polygon overlay, several of the contributors also discuss the performance of other, more substantial, applications.For the research community, the contributors discuss the motivations for and philosophy of their systems. As well, many of the chapters include critiques that complete the research arc by pointing out possible future research directions. Finally, for the object-oriented community, there are many examples of how encapsulation, inheritance, and polymorphism can be used to control the complexity of developing, debugging, and tuning parallel software.

Toward Teraflop Computing & New Grand Challenge Applications Proceedings of the Mardi Gras '94 Conference, February 10-12, 1994 Louisiana State University

This publication contains papers from the Occam User Group (OUG). The main aim of the OUG is to act as an independent forum for the exchange of ideas, results and information in research and development of projects in the area of parallel systems design and programming using various communicating processes oriented approaches for transputer based machines. The papers collected in this volume cover topics such as: methodology of Occam programming, parallel asynchronous algorithms, control of real parallelisms in highly parallel machines of transputers, applications in scientific programming, real-time processing, image processing, etc.

This is the book that will teach programmers to write faster, more efficient code for parallel processors. The reader is introduced to a vast array of procedures and paradigms on which actual coding may be based. Examples and real-life simulations using these devices are presented in C and FORTRAN. The ease in writing code and the satisfaction of running high-performance programs will reward programmers who can learn the tools of presented here.

Parallel distributed processing is transforming the field of cognitive science. Microcognition provides a clear, readable guide to this emerging paradigm from a cognitive philosopher's point of view. It explains and explores the biological basis of PDP, its psychological importance, and its philosophical relevance.