Software -- Programming Languages.

Designing scalable software in C++ requires more than just a sound understanding of logical design. Senior developers, architects, and project leaders need a grasp of high-level physical design concepts that even many software experts have never explored. In Large-Scale C++, Volume I: Process and Architecture , John Lakos takes a practitioner's view of modern large-scale software development, helping experienced professionals apply architectural-level physical design concepts in their everyday work. Lakos teaches critical concepts clearly and concisely, with new high-value examples. Up to date and modular, Large-Scale C++, Volume I, is designed to help you solve problems right now, and serve as an indispensable reference for years to come.

Designing scalable software in C++ requires more than just a sound understanding of logical design. Senior developers, architects, and project leaders need a grasp of high-level physical design concepts that even many software experts have never explored. In Large-Scale C++ Volume I: Process and Architecture, John Lakos takes a practitioner's view of modern large-scale software development, helping experienced professionals apply architectural-level physical design concepts in their everyday work. Lakos teaches critical concepts clearly and concisely, with new high-value examples. Up to date and modular, Large-Scale C++ Volume I is designed to help you solve problems right now, and serve as an appealing reference for years to come.

The purpose of large-scale software architecture is to capture and describe practical representations to make development teams more effective. In this book the authors show how to utilise software architecture as a tool to guide the development instead of capturing the architectural details after all the design decisions have been made. * Offers a concise description of UML usage for large-scale architecture * Discusses software architecture and design principles * Technology and vendor independent

Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors’ papers in top-tier, peer-reviewed, scientific conference proceedings and journals. The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms—such as simulation cloning methods and algorithms—that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena. Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.

Maximize Reward and Minimize Risk with Modern C++ Embracing Modern C++ Safely shows you how to make effective use of the new and enhanced language features of modern C++ without falling victim to their potential pitfalls. Based on their years of experience with large, mission-critical projects, four leading C++ authorities divide C++11/14 language features into three categories: Safe, Conditionally Safe, and Unsafe. Safe features offer compelling value, are easy to use productively, and are relatively difficult to misuse. Conditionally safe features offer significant value but come with risks that require significant expertise and familiarity before use. Unsafe features have an especially poor risk/reward ratio, are easy to misuse, and are beneficial in only the most specialized circumstances. This book distills the C++ community's years of experience applying C++11 and C++14 features and will help you make effective and safe design decisions that reflect real-world, economic engineering tradeoffs in large-scale, diverse software development environments. The authors use examples derived from real code bases to illustrate every finding objectively and to illuminate key issues. Each feature identifies the sound use cases, hidden pitfalls, and shortcomings of that language feature. After reading this book, you will Understand what each C++11/14 feature does and where it works best Recognize how to work around show-stopping pitfalls and annoying corner cases Know which features demand additional training, experience, and peer review Gain insights for preparing coding standards and style guides that suit your organization's needs Be equipped to introduce modern C++ incrementally and judiciously into established code bases Seasoned C++ developers, team leads, and technical managers who want to improve productivity, code quality, and maintainability will find the insights in this modular, meticulously organized reference indispensable. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

State-of-the-Art Approaches to Advance the Large-Scale Green Computing Movement Edited by one of the founders and lead investigator of the Green500 list, The Green Computing Book: Tackling Energy Efficiency at Large Scale explores seminal research in large-scale green computing. It begins with low-level, hardware-based approaches and then traverses up the software stack with increasingly higher-level, software-based approaches. In the first chapter, the IBM Blue Gene team illustrates how to improve the energy efficiency of a supercomputer by an order of magnitude without any system performance loss in parallelizable applications. The next few chapters explain how to enhance the energy efficiency of a large-scale computing system via compiler-directed energy optimizations, an adaptive run-time system, and a general prediction performance framework. The book then explores the interactions between energy management and reliability and describes storage system organization that maximizes energy efficiency and reliability. It also addresses the need for coordinated power control across different layers and covers demand response policies in computing centers. The final chapter assesses the impact of servers on data center costs.