This survey covers a wide range of topics fundamental to calculating integrals on computer systems and discusses both the theoretical and computational aspects of numerical and symbolic methods. It includes extensive sections on one- and multidimensional integration formulas, like polynomial, number-theoretic, and pseudorandom formulas, and deals with issues concerning the construction of numerical integration algorithms.
During the past 20 years, there has been enormous productivity in theoretical as well as computational integration. Some attempts have been made to find an optimal or best numerical method and related computer code to put to rest the problem of numerical integration, but the research is continuously ongoing, as this problem is still very much open-ended. The importance of numerical integration in so many areas of science and technology has made a practical, up-to-date reference on this subject long overdue. The Handbook of Computational Methods for Integration discusses quadrature rules for finite and infinite range integrals and their applications in differential and integral equations, Fourier integrals and transforms, Hartley transforms, fast Fourier and Hartley transforms, Laplace transforms and wavelets. The practical, applied perspective of this book makes it unique among the many theoretical books on numerical integration and quadrature. It will be a welcomed addition to the libraries of applied mathematicians, scientists, and engineers in virtually every discipline.
This book deals with numerical methods that preserve properties of Hamiltonian systems, reversible systems, differential equations on manifolds and problems with highly oscillatory solutions. A complete self-contained theory of symplectic and symmetric methods, which include Runge-Kutta, composition, splitting, multistep and various specially designed integrators, is presented and their construction and practical merits are discussed. The long-time behaviour of the numerical solutions is studied using a backward error analysis (modified equations) combined with KAM theory. The book is illustrated by numerous figures, treats applications from physics and astronomy, and contains many numerical experiments and comparisons of different approaches.
This IBM® Redbooks® publication describes the integration of IBM Platform Symphony® with IBM BigInsightsTM. It includes IBM Platform LSF® implementation scenarios that use IBM System x® technologies. This IBM Redbooks publication is written for consultants, technical support staff, IT architects, and IT specialists who are responsible for providing solutions and support for IBM Platform Computing solutions. This book explains how the IBM Platform Computing solutions and the IBM System x platform can help to solve customer challenges and to maximize systems throughput, capacity, and management. It examines the tools, utilities, documentation, and other resources that are available to help technical teams provide solutions and support for IBM Platform Computing solutions in a System x environment. In addition, this book includes a well-defined and documented deployment model within a System x environment. It provides a planned foundation for provisioning and building large scale parallel high-performance computing (HPC) applications, cluster management, analytics workloads, and grid applications.
In recent years, soft computing techniques have emerged as a successful tool to understand and analyze the collective behavior of service- oriented computing software. Algorithms and mechanisms of self- organization of complex natural systems have been used to solve problems, particularly in complex systems, which are adaptive, ever- evolving, and distributed in nature across the globe. What fits more perfectly into this scenario other than the rapidly developing era of Fog, IoT, and Edge computing environment? Service- oriented computing can be enhanced with soft computing techniques embedded inside the Cloud, Fog, and IoT systems. Soft Computing Principles and Integration for Real-Time Service-Oriented Computing explores soft computing techniques that have wide application in interdisciplinary areas. These soft computing techniques provide an optimal solution to the optimization problem using single or multiple objectives.The book focuses on basic design principles and analysis of soft computing techniques. It discusses how soft computing techniques can be used to improve quality-of-service in serviceoriented architectures. The book also covers applications and integration of soft computing techniques with a service- oriented computing paradigm. Highlights of the book include: A general introduction to soft computing An extensive literature study of soft computing techniques and emerging trends Soft computing techniques based on the principles of artificial intelligence, fuzzy logic, and neural networks The implementation of SOC with a focus on service composition and orchestration, quality of service (QoS) considerations, security and privacy concerns, governance challenges, and the integration of legacy systems The applications of soft computing in adaptive service composition, intelligent service recommendation, fault detection and diagnosis, SLA management, and security Such principles underlying SOC as loose coupling, reusability, interoperability, and abstraction An IoT based framework for real time data collection and analysis using soft computing
This down-to-earth introduction to computation makes use of the broad array of techniques available in the modern computing environment. A self-contained guide for engineers and other users of computational methods, it has been successfully adopted as a text in teaching the next generation of mathematicians and computer graphics majors.
This book constitutes the refereed post-proceedings of the International Conference on Mathematical Modeling and Computational Physics, MMCP 2011, held in Stará Lesná, Slovakia, in July 2011. The 41 revised papers presented were carefully reviewed and selected from numerous submissions. They are organized in topical sections on mathematical modeling and methods, numerical modeling and methods, computational support of the experiments, computing tools, and optimization and simulation.
This first volume in the series "Algorithms and Computation in Mathematics", is destined to become the standard reference work in the field. Manuel Bronstein is the number-one expert on this topic and his book is the first to treat the subject both comprehensively and in sufficient detail - incorporating new results along the way. The book addresses mathematicians and computer scientists interested in symbolic computation, developers and programmers of computer algebra systems as well as users of symbolic integration methods. Many algorithms are given in pseudocode ready for immediate implementation, making the book equally suitable as a textbook for lecture courses on symbolic integration.
This book features the major research advances on integrated networking, caching, and computing. Information-centric networking-based caching is one of the promising techniques for future networks. The cloud computing paradigm has been widely adopted to enable convenient, on-demand network access to a shared pool of configurable computing resources. In addition, fog/edge computing is proposed to deploy computing resources closer to end devices. From the perspective of applications, network, cache and compute are underlying enabling resources. How to manage, control and optimize these resources can have significant impacts on application performance.
Computing systems are ubiquitous in contemporary life. Even the brain is thought to be a computing system of sorts. But what does it mean to say that a given organ or system "computes"? What is it about laptops, smartphones, and nervous systems that they are deemed to compute - and why does itseldom occur to us to describe stomachs, hurricanes, rocks, or chairs that way? These questions are key to laying the conceptual foundations of computational sciences, including computer science and engineering, and the cognitive and neural sciences.Oron Shagrir here provides an extended argument for the semantic view of computation, which states that semantic properties are involved in the nature of computing systems. The first part of the book provides general background. Although different in scope, these chapters have a common theme-namely,that the linkage between the mathematical theory of computability and the notion of physical computation is weak. The second part of the book reviews existing non-semantic accounts of physical computation. Shagrir analyze three influential accounts in greater depth and argues that none of theseaccounts is satisfactory, but each of them highlights certain key features of physical computation that he eventually adopts in his own semantic account of physical computation - a view that rests on a phenomenon known as simultaneous implementation (or "indeterminacy of computation"). Shagrircompletes the characterization of his account of computation and highlights the distinctive feature of computational explanations.
