Parallel Scientific Computing

There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.

New approaches to parallel computing are being developed that make better use of the heterogeneous cluster architecture Provides a detailed introduction to parallel computing on heterogenous clusters All concepts and algorithms are illustrated with working programs that can be compiled and executed on any cluster The algorithms discussed have practical applications in a range of real-life parallel computing problems, such as the N-body problem, portfolio management, and the modeling of oil extraction

Discover how to streamline complex bioinformatics applications with parallel computing This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution. A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster rates of computation. Current parallel computing techniques and technologies are examined, including distributed computing and grid computing. Readers are provided with a mixture of algorithms, experiments, and simulations that provide not only qualitative but also quantitative insights into the dynamic field of bioinformatics. Parallel Computing for Bioinformatics and Computational Biology is a contributed work that serves as a repository of case studies, collectively demonstrating how parallel computing streamlines difficult problems in bioinformatics and produces better results. Each of the chapters is authored by an established expert in the field and carefully edited to ensure a consistent approach and high standard throughout the publication. The work is organized into five parts: * Algorithms and models * Sequence analysis and microarrays * Phylogenetics * Protein folding * Platforms and enabling technologies Researchers, educators, and students in the field of bioinformatics will discover how high-performance computing can enable them to handle more complex data sets, gain deeper insights, and make new discoveries.

This book provides the mathematical basis for investigating numerically equations from physics, life sciences or engineering. Tools for analysis and algorithms are confronted to a large set of relevant examples that show the difficulties and the limitations of the most na?ve approaches. These examples not only provide the opportunity to put into practice mathematical statements, but modeling issues are also addressed in detail, through the mathematical perspective.

An invaluable reference for anyone designing new parallel or distributed systems. Includes detailed case studies of specific systems from Stanford, MIT, and other leading research universities. The authors emphasize performance, surveying all available techniques.

Written by one of the few top internationally recognized experts in the field, this book concentrates on those topics that will remain fundamental, such as low power computing, reversible programming languages, and applications in thermodynamics. It describes reversible computing from various points of view: Boolean algebra, group theory, logic circuits, low-power electronics, communication, software, quantum computing. It is this multidisciplinary approach that makes it unique. Backed by numerous examples, this is useful for all levels of the scientific and academic community, from undergraduates to established academics.

Summarizes the current state and upcoming trends within the area of fog computing Written by some of the leading experts in the field, Fog Computing: Theory and Practice  focuses on the technological aspects of employing fog computing in various application domains, such as smart healthcare, industrial process control and improvement, smart cities, and virtual learning environments. In addition, the Machine-to-Machine (M2M) communication methods for fog computing environments are covered in depth. Presented in two parts—Fog Computing Systems and Architectures, and Fog Computing Techniques and Application—this book covers such important topics as energy efficiency and Quality of Service (QoS) issues, reliability and fault tolerance, load balancing, and scheduling in fog computing systems. It also devotes special attention to emerging trends and the industry needs associated with utilizing the mobile edge computing, Internet of Things (IoT), resource and pricing estimation, and virtualization in the fog environments. Includes chapters on deep learning, mobile edge computing, smart grid, and intelligent transportation systems beyond the theoretical and foundational concepts Explores real-time traffic surveillance from video streams and interoperability of fog computing architectures Presents the latest research on data quality in the IoT, privacy, security, and trust issues in fog computing Fog Computing: Theory and Practice provides a platform for researchers, practitioners, and graduate students from computer science, computer engineering, and various other disciplines to gain a deep understanding of fog computing.

The primary purpose of this book is to capture the state-of-the-art in Cloud Computing technologies and applications. The book will also aim to identify potential research directions and technologies that will facilitate creation a global market-place of cloud computing services supporting scientific, industrial, business, and consumer applications. We expect the book to serve as a reference for larger audience such as systems architects, practitioners, developers, new researchers and graduate level students. This area of research is relatively recent, and as such has no existing reference book that addresses it. This book will be a timely contribution to a field that is gaining considerable research interest, momentum, and is expected to be of increasing interest to commercial developers. The book is targeted for professional computer science developers and graduate students especially at Masters level. As Cloud Computing is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years, its knowledge will help position our readers at the forefront of the field.

This book provides an introduction to the complex field of ubiquitous computing Ubiquitous Computing (also commonly referred to as Pervasive Computing) describes the ways in which current technological models, based upon three base designs: smart (mobile, wireless, service) devices, smart environments (of embedded system devices) and smart interaction (between devices), relate to and support a computing vision for a greater range of computer devices, used in a greater range of (human, ICT and physical) environments and activities. The author details the rich potential of ubiquitous computing, the challenges involved in making it a reality, and the prerequisite technological infrastructure. Additionally, the book discusses the application and convergence of several current major and future computing trends. Key Features: Provides an introduction to the complex field of ubiquitous computing Describes how current technology models based upon six different technology form factors which have varying degrees of mobility wireless connectivity and service volatility: tabs, pads, boards, dust, skins and clay, enable the vision of ubiquitous computing Describes and explores how the three core designs (smart devices, environments and interaction) based upon current technology models can be applied to, and can evolve to, support a vision of ubiquitous computing and computing for the future Covers the principles of the following current technology models, including mobile wireless networks, service-oriented computing, human computer interaction, artificial intelligence, context-awareness, autonomous systems, micro-electromechanical systems, sensors, embedded controllers and robots Covers a range of interactions, between two or more UbiCom devices, between devices and people (HCI), between devices and the physical world. Includes an accompanying website with PowerPoint slides, problems and solutions, exercises, bibliography and further reading Graduate students in computer science, electrical engineering and telecommunications courses will find this a fascinating and useful introduction to the subject. It will also be of interest to ICT professionals, software and network developers and others interested in future trends and models of computing and interaction over the next decades.