Kategoria BISAC: Computers >> Distributed Systems - General

Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers.

The text first introduces the architecture of modern cache-based microprocessors and...

This book describes the coarray parallel programming model that will be part of the next standard version of the Fortran language. It provides a practical guide for Fortran programmers who want to start writing parallel applications using coarrays as soon as the compilers become commercially available. The authors present the technical specification of the coarray model in enough detail for programmers to write standard-conforming code. They also offer a large number of examples of parallel algorithms written in the coarray model and include exercises with solutions. A supplementary...

Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems.

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If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.

With this practical book, you'll discover how to catch complications in your distributed system before they develop into costly problems. Based on his extensive experience in systems ops at large technology companies, author Slawek Ligus describes an effective data-driven approach for monitoring and alerting that enables you to maintain high availability and deliver a high quality of service.

Learn methods for measuring state changes and data flow in your system, and set up alerts to help you recover quickly from problems when they do arise. If you're a system operator waging the...

If you have a working knowledge of Haskell, this hands-on book shows you how to use the language's many APIs and frameworks for writing both parallel and concurrent programs. You'll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions.

Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises...

Desktop Grid Computing presents common techniques used in numerous models, algorithms, and tools developed during the last decade to implement desktop grid computing. These techniques enable the solution of many important sub-problems for middleware design, including scheduling, data management, security, load balancing, result certification, and fault tolerance.

The book s first part covers the initial ideas and basic concepts of desktop grid computing. The second part explores challenging current and future problems. Each chapter presents the sub-problems,...

Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you're using.

Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations,...

The rapid and widespread acceptance of shared-memory multiprocessor architectures has created a pressing demand for an efficient way to program these systems. At the same time, developers of technical and scientific applications in industry and in government laboratories find they need to parallelize huge volumes of code in a portable fashion. OpenMP, developed jointly by several parallel computing vendors to address these issues, is an industry-wide standard for programming shared-memory and distributed shared-memory multiprocessors. It consists of a set of compiler directives and...