Applied Parallel Computing

CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC facility. As a result, CUDA is increasingly important in scientific and technical computing across the whole STEM community, from medical physics and financial modelling to big data applications and beyond. This unique book on CUDA draws on the author's passion for and long experience of developing and using computers to acquire and analyse scientific data. The result is an innovative text featuring a much richer set of examples than found in any other comparable book on GPU computing. Much attention has been paid to the C++ coding style, which is compact, elegant and efficient. A code base of examples and supporting material is available online, which readers can build on for their own projects.

Computing and Coding in the Real World looks at applied coding and the computation hidden in the world that surrounds us. Readers will learn how things work, from scanners at supermarket checkouts to

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-s

This book constitutes the proceedings of the 14th International Conference on Applied Reconfigurable Computing, ARC 2018, held in Santorini, Greece, in May 2018. The 29 full papers and 22 short

This book presents extended versions of papers originally presented and discussed at the 3rd International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2016) held from August 1

Designed for introductory parallel computing courses at the advanced undergraduate or beginning graduate level, Elements of Parallel Computing presents the fundamental concepts of parallel computing n

This book fills a unique gap. While topical books exist for parallel programming, high performance computing, programming languages, molecular simulation theory, DFT and specific developer tools, none

This book presents a variety of applied mathematics topics with an emphasis on problem solving techniques using MATLAB. Numerous examples are presented as illustrations of basic concepts and problem s

This book constitutes the thoroughly refereed post-conference proceedings of the 28th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2015, held in Raleigh, NC, USA, in

The book contains the extended version of the works that have been presented and discussed in the Second International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2015) held d

The book contains the extended version of the works that have been presented and discussed in the Second International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2015) held d

The two volumes LNCS 8805 and 8806 constitute the thoroughly refereed post-conference proceedings of 18 workshops held at the 20th International Conference on Parallel Computing, Euro-Par 2014, in Por

This book constitutes the thoroughly refereed post-conference proceedings of the 26th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2013, held in Tokyo, Japan, in Sept

Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Acce

The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.

The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.

This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.

Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many st

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics,

Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many st

Despite five decades of research, parallel computing remains an exotic, frontier technology on the fringes of mainstream computing. Its much-heralded triumph over sequential computing has yet to mater

Thirty years ago mathematical, as opposed to applied numerical, computation was difficult to perform and so relatively little used. Three threads changed that: the emergence of the personal computer;

In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. I

This two-volume-set (LNCS 7203 and 7204) constitutes the refereed proceedings of the 9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011, held in Torun, Poland, in S

This two-volume-set (LNCS 7203 and 7204) constitutes the refereed proceedings of the 9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011, held in Torun, Poland, in S

Designed for researchers, engineers, IT professionals, and graduate students in parallel and cloud computing, this volume covers the state of the art in cloud computing theory and practice. It spans t

Thirty years ago mathematical, as opposed to applied numerical, computation was difficult to perform and so relatively little used. Three threads changed that: the emergence of the personal computer;

The arrival and popularity of multi-core processors has sparked a renewed interest in the development of parallel programs. Similarly, the availability of low-cost microprocessors and sensors has generated a great interest in embedded real-time programs. This book provides students and programmers whose backgrounds are in traditional sequential programming with the opportunity to expand their capabilities into parallel, embedded, real-time and distributed computing. It also addresses the theoretical foundation of real-time scheduling analysis, focusing on theory that is useful for actual applications. Written by award-winning educators at a level suitable for undergraduates and beginning graduate students, this book is the first truly entry-level textbook in the subject. Complete examples allow readers to understand the context in which a new concept is used, and enable them to build and run the examples, make changes, and observe the results.