With the rising importance of multilingualism in language industries, brought about by global markets and world-wide information exchange, parallel corpora, i.e. corpora of texts accompanied by their translation, have become key resources in the development of natural language processing tools. The applications based upon parallel corpora are numerous and growing in number: multilingual lexicography and terminology, machine and human translation, cross-language information retrieval, language learning, etc. The book's chapters have been commissioned from major figures in the field of parallel corpus building and exploitation, with the aim of showing the state of the art in parallel text alignment and use ten to fifteen years after the first parallel-text alignment techniques were developed. Within the book, the following broad themes are addressed: (i) techniques for the alignment of parallel texts at various levels such as sentence, clause, and word; (ii) the use of parallel texts in fields as diverse as translation, lexicography, and information retrieval; (iii) available corpus resources and the evaluation of alignment methods. The book will be of interest to researchers and advanced students of computational linguistics, terminology, lexicography and translation, both in academia and industry.

l This book evolved from the ARCADE evaluation exercise that started in 1995. The project's goal is to evaluate alignment systems for parallel texts, i. e. , texts accompanied by their translation. Thirteen teams from various places around the world have participated so far and for the first time, some ten to fifteen years after the first alignment techniques were designed, the community has been able to get a clear picture of the behaviour of alignment systems. Several chapters in this book describe the details of competing systems, and the last chapter is devoted to the description of the evaluation protocol and results. The remaining chapters were especially commissioned from researchers who have been major figures in the field in recent years, in an attempt to address a wide range of topics that describe the state of the art in parallel text processing and use. As I recalled in the introduction, the Rosetta stone won eternal fame as the prototype of parallel texts, but such texts are probably almost as old as the invention of writing. Nowadays, parallel texts are electronic, and they are be coming an increasingly important resource for building the natural language processing tools needed in the "multilingual information society" that is cur rently emerging at an incredible speed. Applications are numerous, and they are expanding every day: multilingual lexicography and terminology, machine and human translation, cross-language information retrieval, language learning, etc.

This text provides one of the broadest presentations of parallel processing available, including the structure of parallelprocessors and parallel algorithms. The emphasis is on mapping algorithms to highly parallel computers, with extensive coverage of array and multiprocessor architectures. Early chapters provide insightful coverage on the analysis of parallel algorithms and program transformations, effectively integrating a variety of material previously scattered throughout the literature. Theory and practice are well balanced across diverse topics in this concise presentation. For exceptional clarity and comprehension, the author presents complex material in geometric graphs as well as algebraic notation. Each chapter includes well-chosen examples, tables summarizing related key concepts and definitions, and a broad range of worked exercises. - Overview of common hardware and theoretical models, including algorithm characteristics and impediments to fast performance - Analysis of data dependencies and inherent parallelism through program examples, building from simple to complex - Graphic and explanatory coverage of program transformations - Easy-to-follow presentation of parallel processor structures and interconnection networks, including parallelizing and restructuring compilers - Parallel synchronization methods and types of parallel operating systems - Detailed descriptions of hypercube systems - Specialized chapters on dataflow and on AI architectures

This book is an introduction to the highly topical areas of distributed and parallel processing, and will be of value to computer science undergraduates, students of electrical engineering, electronics and microprocessors, and non-specialist professionals working in related areas.

Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.

THE CONTEXT OF PARALLEL PROCESSING The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, and theoretical studies, the design of an instruction-set architecture, once considered an art, has been transformed into one of the most quantitative branches of computer technology. At the same time, better understanding of various forms of concurrency, from standard pipelining to massive parallelism, and invention of architectural structures to support a reasonably efficient and user-friendly programming model for such systems, has allowed hardware performance to continue its exponential growth. This trend is expected to continue in the near future. This explosive growth, linked with the expectation that performance will continue its exponential rise with each new generation of hardware and that (in stark contrast to software) computer hardware will function correctly as soon as it comes off the assembly line, has its down side. It has led to unprecedented hardware complexity and almost intolerable dev- opment costs. The challenge facing current and future computer designers is to institute simplicity where we now have complexity; to use fundamental theories being developed in this area to gain performance and ease-of-use benefits from simpler circuits; to understand the interplay between technological capabilities and limitations, on the one hand, and design decisions based on user and application requirements on the other.

Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing