No single solution applied at one particular layer can help applications solve all performance-related issues with communication services. Instead, this book shows that a coordinated effort is needed among the layers. It covers many different types of technologies and layers across the stack, from the architectural features of the hardware, through the protocols and their implementation in operating system kernels, to the manner in which application services and middleware are using underlying platforms. The book also describes key developments in high-end platforms, high performance interconnection fabrics and communication libraries, and multi- and many-core systems.

In seven chapters, Dr. Gerson addresses the most troubling issues related to performance including the difference between positive and negative performance motivation, the characteristics of high performers, the role of proper goal and objective setting, planning for high performance, eliminating self-limiting beliefs, and making incentives real.

This book introduces the state-of-the-art in research in parallel and distributed embedded systems, which have been enabled by developments in silicon technology, micro-electro-mechanical systems (MEMS), wireless communications, computer networking, and digital electronics. These systems have diverse applications in domains including military and defense, medical, automotive, and unmanned autonomous vehicles. The emphasis of the book is on the modeling and optimization of emerging parallel and distributed embedded systems in relation to the three key design metrics of performance, power and dependability. Key features: Includes an embedded wireless sensor networks case study to help illustrate the modeling and optimization of distributed embedded systems. Provides an analysis of multi-core/many-core based embedded systems to explain the modeling and optimization of parallel embedded systems. Features an application metrics estimation model; Markov modeling for fault tolerance and analysis; and queueing theoretic modeling for performance evaluation. Discusses optimization approaches for distributed wireless sensor networks; high-performance and energy-efficient techniques at the architecture, middleware and software levels for parallel multicore-based embedded systems; and dynamic optimization methodologies. Highlights research challenges and future research directions. The book is primarily aimed at researchers in embedded systems; however, it will also serve as an invaluable reference to senior undergraduate and graduate students with an interest in embedded systems research.

The design, construction, operation, and retrofit of buildings is evolving in response to ever-increasing knowledge about the impact of indoor environments on people and the impact of buildings on the environment. Research has shown that the quality of indoor environments can affect the health, safety, and productivity of the people who occupy them. Buildings are also resource intensive, accounting for 40 percent of primary energy use in the United States, 12 percent of water consumption, and 60 percent of all non-industrial waste. The processes for producing electricity at power plants and delivering it for use in buildings account for 40 percent of U.S. greenhouse gas emissions. The U.S. federal government manages approximately 429,000 buildings of many types with a total square footage of 3.34 billion worldwide, of which about 80 percent is owned space. More than 30 individual departments and agencies are responsible for managing these buildings. The characteristics of each agency's portfolio of facilities are determined by its mission and its programs. In 2010, GSA's Office of Federal High-Performance Green Buildings asked the National Academies to appoint an ad hoc committee of experts to conduct a public workshop and prepare a report that identified strategies and approaches for achieving a range of objectives associated with high-performance green federal buildings. Achieving High-Performance Federal Facilities identifies examples of important initiatives taking place and available resources. The report explores how these examples could be used to help make sustainability the preferred choice at all levels of decision making. Achieving High-Performance Federal Facilities can serve as a valuable guide federal agencies with differing missions, types of facilities, and operating procedures.

Are you looking to take the next step in your career? Can you manage yourself with ease, but need more confidence when managing others? Achieving excellence as a manager requires a broad skillset, and The Essential Manager’s Handbook provides easy-to-follow and engaging advice on the 6 key areas. Nurture your confidence with managing people, leadership, achieving high performance, effective communication, presenting, and negotiating. With key quotes, bright visuals, and breakdowns by subject, this book is accessible and easy-to-use. Interactive tips and checklists will encourage you to note down your thoughts, examining past and present workplace experiences that you can learn from. Expert insights from management professionals and step-by-step instructions will help you understand how to deal with challenges and gain valuable management skills for life. This accessible and clear guide is packed with practical, no-nonsense information covering everything you need to know about acquiring and developing management skills. Pick up The Essential Manager’s Handbook for quick reference when you’re in need of guidance or work through each section at your own pace to become the best manager you can be. Series Overview: DK's Essential Managers series contains the know-how you need to be a more effective manager and hone your management style, covering a range of essential topics, from managing, coaching, and mentoring teams and individuals to time management, communication, leadership, and strategic thinking. Each guide is clearly presented for ease of reference, with visual pointers, tips, and infographics.

LNCS volumes 2073 and 2074 contain the proceedings of the International Conference on Computational Science, ICCS 2001, held in San Francisco, California, May 27 -31, 2001. The two volumes consist of more than 230 contributed and invited papers that reflect the aims of the conference to bring together researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering advanced application of computational methods to sciences such as physics, chemistry, life sciences, and engineering, arts and humanitarian fields, along with software developers and vendors, to discuss problems and solutions in the area, to identify new issues, and to shape future directions for research, as well as to help industrial users apply various advanced computational techniques.

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.