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.

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.

並行和分散系統（PADS）已從計算科學和超級計算機的早期發展到各種新穎的計算範式，每個範式都被用於解決特定的問題或應用需求，包括分散系統、並行計算和集群計算，通常稱為高性能計算（HPC）。網格、雲和霧計算模式是這些PADS範式中最重要的，它們在實踐中共享共同的概念。

在當今這個埃克斯級計算機時代，許多核心架構、多核集群超級計算機和雲計算範式極大地影響了計算在科學和學術界（例如科學計算和大規模模擬）中的應用方式。《實施並行和分散系統》介紹了一個名為Parvicursor的PADS基礎設施，可以促進構建可擴展和高性能的並行分散系統，如HPC、網格和雲計算。

本書涵蓋了在構建分散和HPC系統中使用的並行編程模型、技術、工具、開發框架和高級概念。它為在分散環境中開發高性能客戶端-服務器應用程序提供了一個路線圖，並提供了構建本地和面向對象的C++平台的逐步程序。

特點：
- 並行性的硬件和軟件觀點
- 並行編程多核處理器、計算機網絡和存儲系統
- Parvicursor.NET Framework：.NET Framework的部分、本地和跨平台C++實現
- xThread：結合線程級並行性和分散內存編程模型的分布式線程編程模型
- xDFS：用於高效文件傳輸的本地跨平台框架
- 使用消息傳遞接口（MPI）進行HPC系統和超級計算機的並行編程

本書著重於利用多核處理器和尖端系統單晶片（SoC）架構的計算能力來實現數據傳輸速度，並解釋了如何實現節能的基礎設施，並檢查如何在雲節點之間分配線程。本書以堅實的設計和實施方法為基礎，是設計、實施和部署這些非常複雜系統的完整參考資料。

Alireza Poshtkohi applies computer science and mathematics to tackle grand research challenges in engineering, physics, and medicine. He has worked internationally in both academia and industry in many different roles ranging from computer scientist, neuroscientist, university lecturer, electronics engineer, software engineer, IT consultant and data centre architect, to full-stack developer. He holds BSc and MSc degrees and a PhD in electrical and electronics engineering and computational neuroscience, respectively. To date, he has taught 17 courses--such as parallel algorithms, advanced algorithms, operating systems, and computer networks, to name just a few--in electrical and computer engineering departments at different universities. His current research interests include applied mathematics, biophysics, high-performance computing, and theoretical physics.

M. B. Ghaznavi-Ghoushchi holds a BSc degree from Shiraz University, Shiraz, Iran (1993), and MSc and PhD both from Tarbiat Modares University (TMU), Tehran, Iran, in 1997 and 2003, respectively. During 2003-2004, he was a researcher at TMU Institute of Information Technology. He is the founder and director of High-Performance and Cloud Computing (HPCC) and Integrated Circuits and Systems (ICS) laboratories at Shahed University. He is currently an associate professor at Shahed University, Tehran, Iran. His interests include VLSI Design; Low Power and Energy-Efficient circuits and systems; Computer-Aided Design Automation for Mixed Signal; and UML-based designs for SoC and Mixed-Signal.

Alireza Poshtkohi將計算機科學和數學應用於解決工程、物理和醫學領域的重大研究挑戰。他曾在學術界和工業界國際間工作，擔任過多種不同的角色，包括計算機科學家、神經科學家、大學講師、電子工程師、軟體工程師、IT顧問和數據中心架構師，以及全棧開發人員。他分別擁有學士和碩士學位，以及電氣與電子工程和計算神經科學的博士學位。迄今為止，他在不同大學的電氣與計算機工程系教授了17門課程，包括並行算法、高級算法、操作系統和計算機網絡等。他目前的研究興趣包括應用數學、生物物理學、高性能計算和理論物理。

M. B. Ghaznavi-Ghoushchi於1993年在伊朗設拉子大學獲得學士學位，並於1997年和2003年分別在伊朗塔比亞特·莫達雷斯大學獲得碩士和博士學位。在2003年至2004年期間，他在該大學的信息技術研究所擔任研究員。他是伊朗沙希德大學高性能和雲計算（HPCC）實驗室和集成電路和系統（ICS）實驗室的創始人和主任。他目前是伊朗德黑蘭沙希德大學的副教授。他的研究興趣包括VLSI設計、低功耗和節能電路和系統、混合信號的計算機輔助設計自動化，以及基於UML的SoC和混合信號設計。