دانلود کتاب Implementing Parallel and Distributed Systems

Parallel and distributed systems (PADS) have evolved from the early days of computational science and supercomputers to a wide range of novel computing paradigms, each of which is exploited to tackle specific problems or application needs, including distributed systems, parallel computing, and cluster computing, generally called high-performance computing (HPC). Grid, Cloud, and Fog computing patterns are the most important of these PADS paradigms, which share common concepts in practice.

Many-core architectures, multi-core cluster-based supercomputers, and Cloud Computing paradigms in this era of exascale computers have tremendously influenced the way computing is applied in science and academia (e.g., scientific computing and large-scale simulations). Implementing Parallel and Distributed Systems presents a PADS infrastructure known as Parvicursor that can facilitate the construction of such scalable and high-performance parallel distributed systems as HPC, Grid, and Cloud Computing.

This book covers parallel programming models, techniques, tools, development frameworks, and advanced concepts of parallel computer systems used in the construction of distributed and HPC systems. It specifies a roadmap for developing high-performance client-server applications for distributed environments and supplies step-by-step procedures for constructing a native and object-oriented C++ platform.

Parvicursor project is an essential effort to establish an OS-based framework to fast develop new high-performance distributed paradigms. The basic infrastructure is inspired by concepts mostly available in Cluster, Grid, and Cloud environments. From the viewpoint of the developer users, the Parvicursor.NET Framework provides a set of rich, cross-platform, object-oriented, high-performance, and low-level C++ class libraries which enable quick and solid development of the next-generation networked/distributed applications and paradigms. From the viewpoint of the Parvicursor core, it supplies some critical services developed with parts in kernel mode and some other parts in userspace. In the Chapter 8, we briefly introduce the .NET Framework and existing technologies within the platform. The presented material herein will make the understanding of the Parvicursor.NET Framework more tangible to the reader. In this section, we examine a practical example as an attempt to describe how porting the Microsoft .NET Framework classes written in C# language into native code through the standard C++ for Parvicursor.NET Framework is achieved. At the end, we point out a lot of technical points for developers targeting the Parvicursor platform in porting their applications from C# to native C++.

Features:

Hardware and software perspectives on parallelism
Parallel programming many-core processors, computer networks and storage systems
Parvicursor.NET Framework: a partial, native, and cross-platform C++ implementation of the .NET Framework
xThread: a distributed thread programming model by combining thread-level parallelism and distributed memory programming models
xDFS: a native cross-platform framework for efficient file transfer
Parallel programming for HPC systems and supercomputers using message passing interface (MPI)

Focusing on data transmission speed that exploits the computing power of multicore processors and cutting-edge system-on-chip (SoC) architectures, it explains how to implement an energy-efficient infrastructure and examines distributing threads amongst Cloud nodes. Taking a solid approach to design and implementation, this book is a complete reference for designing, implementing, and deploying these very complicated systems.