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| openmp book: Parallel Programming in OpenMP Rohit Chandra, 2001 Software -- Programming Techniques. |
| openmp book: Parallel Programming in C with MPI and OpenMP Michael Jay Quinn, 2004 The era of practical parallel programming has arrived, marked by the popularity of the MPI and OpenMP software standards and the emergence of commodity clusters as the hardware platform of choice for an increasing number of organizations. This exciting new book,Parallel Programming in C with MPI and OpenMPaddresses the needs of students and professionals who want to learn how to design, analyze, implement, and benchmark parallel programs in C using MPI and/or OpenMP. It introduces a rock-solid design methodology with coverage of the most important MPI functions and OpenMP directives. It also demonstrates, through a wide range of examples, how to develop parallel programs that will execute efficiently on today’s parallel platforms. If you are an instructor who has adopted the book and would like access to the additional resources, please contact your local sales rep. or Michelle Flomenhoft at: michelle_flomenhoft@mcgraw-hill.com. |
| openmp book: Using OpenMP-The Next Step Ruud Van Der Pas, Eric Stotzer, Christian Terboven, 2017-10-20 A guide to the most recent, advanced features of the widely used OpenMP parallel programming model, with coverage of major features in OpenMP 4.5. This book offers an up-to-date, practical tutorial on advanced features in the widely used OpenMP parallel programming model. Building on the previous volume, Using OpenMP: Portable Shared Memory Parallel Programming (MIT Press), this book goes beyond the fundamentals to focus on what has been changed and added to OpenMP since the 2.5 specifications. It emphasizes four major and advanced areas: thread affinity (keeping threads close to their data), accelerators (special hardware to speed up certain operations), tasking (to parallelize algorithms with a less regular execution flow), and SIMD (hardware assisted operations on vectors). As in the earlier volume, the focus is on practical usage, with major new features primarily introduced by example. Examples are restricted to C and C++, but are straightforward enough to be understood by Fortran programmers. After a brief recap of OpenMP 2.5, the book reviews enhancements introduced since 2.5. It then discusses in detail tasking, a major functionality enhancement; Non-Uniform Memory Access (NUMA) architectures, supported by OpenMP; SIMD, or Single Instruction Multiple Data; heterogeneous systems, a new parallel programming model to offload computation to accelerators; and the expected further development of OpenMP. |
| openmp book: Using OpenMP Barbara Chapman, Gabriele Jost, Ruud Van Der Pas, 2007-10-12 A comprehensive overview of OpenMP, the standard application programming interface for shared memory parallel computing—a reference for students and professionals. I hope that readers will learn to use the full expressibility and power of OpenMP. This book should provide an excellent introduction to beginners, and the performance section should help those with some experience who want to push OpenMP to its limits. —from the foreword by David J. Kuck, Intel Fellow, Software and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation OpenMP, a portable programming interface for shared memory parallel computers, was adopted as an informal standard in 1997 by computer scientists who wanted a unified model on which to base programs for shared memory systems. OpenMP is now used by many software developers; it offers significant advantages over both hand-threading and MPI. Using OpenMP offers a comprehensive introduction to parallel programming concepts and a detailed overview of OpenMP. Using OpenMP discusses hardware developments, describes where OpenMP is applicable, and compares OpenMP to other programming interfaces for shared and distributed memory parallel architectures. It introduces the individual features of OpenMP, provides many source code examples that demonstrate the use and functionality of the language constructs, and offers tips on writing an efficient OpenMP program. It describes how to use OpenMP in full-scale applications to achieve high performance on large-scale architectures, discussing several case studies in detail, and offers in-depth troubleshooting advice. It explains how OpenMP is translated into explicitly multithreaded code, providing a valuable behind-the-scenes account of OpenMP program performance. Finally, Using OpenMP considers trends likely to influence OpenMP development, offering a glimpse of the possibilities of a future OpenMP 3.0 from the vantage point of the current OpenMP 2.5. With multicore computer use increasing, the need for a comprehensive introduction and overview of the standard interface is clear. Using OpenMP provides an essential reference not only for students at both undergraduate and graduate levels but also for professionals who intend to parallelize existing codes or develop new parallel programs for shared memory computer architectures. |
| openmp book: An Introduction to Parallel Programming Peter Pacheco, 2011-02-17 An Introduction to Parallel Programming is the first undergraduate text to directly address compiling and running parallel programs on the new multi-core and cluster architecture. It explains how to design, debug, and evaluate the performance of distributed and shared-memory programs. The author Peter Pacheco uses a tutorial approach to show students how to develop effective parallel programs with MPI, Pthreads, and OpenMP, starting with small programming examples and building progressively to more challenging ones. The text is written for students in undergraduate parallel programming or parallel computing courses designed for the computer science major or as a service course to other departments; professionals with no background in parallel computing. - Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples - Focuses on designing, debugging and evaluating the performance of distributed and shared-memory programs - Explains how to develop parallel programs using MPI, Pthreads, and OpenMP programming models |
| openmp book: High Performance Parallel Runtimes Michael Klemm, Jim Cownie, 2021-02-08 This book focuses on the theoretical and practical aspects of parallel programming systems for today's high performance multi-core processors and discusses the efficient implementation of key algorithms needed to implement parallel programming models. Such implementations need to take into account the specific architectural aspects of the underlying computer architecture and the features offered by the execution environment. This book briefly reviews key concepts of modern computer architecture, focusing particularly on the performance of parallel codes as well as the relevant concepts in parallel programming models. The book then turns towards the fundamental algorithms used to implement the parallel programming models and discusses how they interact with modern processors. While the book will focus on the general mechanisms, we will mostly use the Intel processor architecture to exemplify the implementation concepts discussed but will present other processor architectures where appropriate. All algorithms and concepts are discussed in an easy to understand way with many illustrative examples, figures, and source code fragments. The target audience of the book is students in Computer Science who are studying compiler construction, parallel programming, or programming systems. Software developers who have an interest in the core algorithms used to implement a parallel runtime system, or who need to educate themselves for projects that require the algorithms and concepts discussed in this book will also benefit from reading it. You can find the source code for this book at https://github.com/parallel-runtimes/lomp. |
| openmp book: Parallel and High Performance Computing Robert Robey, Yuliana Zamora, 2021-08-24 Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code |
| openmp book: Parallel Programming Bertil Schmidt, Jorge Gonzalez-Martinez, Christian Hundt, Moritz Schlarb, 2017-11-20 Parallel Programming: Concepts and Practice provides an upper level introduction to parallel programming. In addition to covering general parallelism concepts, this text teaches practical programming skills for both shared memory and distributed memory architectures. The authors' open-source system for automated code evaluation provides easy access to parallel computing resources, making the book particularly suitable for classroom settings. - Covers parallel programming approaches for single computer nodes and HPC clusters: OpenMP, multithreading, SIMD vectorization, MPI, UPC++ - Contains numerous practical parallel programming exercises - Includes access to an automated code evaluation tool that enables students the opportunity to program in a web browser and receive immediate feedback on the result validity of their program - Features an example-based teaching of concept to enhance learning outcomes |
| openmp book: Structured Parallel Programming Michael McCool, James Reinders, Arch Robison, 2012-06-25 Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers |
| openmp book: Introduction to High Performance Computing for Scientists and Engineers Georg Hager, Gerhard Wellein, 2010-07-02 Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author |
| openmp book: Using OpenCL J. Kowalik, T. Puźniakowski, 2012-02-29 In 2011 many computer users were exploring the opportunities and the benefits of the massive parallelism offered by heterogeneous computing. In 2000 the Khronos Group, a not-for-profit industry consortium, was founded to create standard open APIs for parallel computing, graphics and dynamic media. Among them has been OpenCL, an open system for programming heterogeneous computers with components made by multiple manufacturers. This publication explains how heterogeneous computers work and how to program them using OpenCL. It also describes how to combine OpenCL with OpenGL for displaying graphical effects in real time. Chapter 1 describes briefly two older de facto standard and highly successful parallel programming systems: MPI and OpenMP. Collectively, the MPI, OpenMP, and OpenCL systems cover programming of all major parallel architectures: clusters, shared-memory computers, and the newest heterogeneous computers. Chapter 2, the technical core of the book, deals with OpenCL fundamentals: programming, hardware, and the interaction between them. Chapter 3 adds important information about such advanced issues as double-versus-single arithmetic precision, efficiency, memory use, and debugging. Chapters 2 and 3 contain several examples of code and one case study on genetic algorithms. These examples are related to linear algebra operations, which are very common in scientific, industrial, and business applications. Most of the book’s examples can be found on the enclosed CD, which also contains basic projects for Visual Studio, MinGW, and GCC. This supplementary material will assist the reader in getting a quick start on OpenCL projects. |
| openmp book: Multicore and GPU Programming Gerassimos Barlas, 2014-12-16 Multicore and GPU Programming offers broad coverage of the key parallel computing skillsets: multicore CPU programming and manycore massively parallel computing. Using threads, OpenMP, MPI, and CUDA, it teaches the design and development of software capable of taking advantage of today's computing platforms incorporating CPU and GPU hardware and explains how to transition from sequential programming to a parallel computing paradigm. Presenting material refined over more than a decade of teaching parallel computing, author Gerassimos Barlas minimizes the challenge with multiple examples, extensive case studies, and full source code. Using this book, you can develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting multicore machines. - Comprehensive coverage of all major multicore programming tools, including threads, OpenMP, MPI, and CUDA - Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance - Particular focus on the emerging area of divisible load theory and its impact on load balancing and distributed systems - Download source code, examples, and instructor support materials on the book's companion website |
| openmp book: Programming Models for Parallel Computing Pavan Balaji, 2015-11-06 An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng |
| openmp book: Using Advanced MPI William Gropp, Torsten Hoefler, Rajeev Thakur, Ewing Lusk, 2014-11-07 A guide to advanced features of MPI, reflecting the latest version of the MPI standard, that takes an example-driven, tutorial approach. This book offers a practical guide to the advanced features of the MPI (Message-Passing Interface) standard library for writing programs for parallel computers. It covers new features added in MPI-3, the latest version of the MPI standard, and updates from MPI-2. Like its companion volume, Using MPI, the book takes an informal, example-driven, tutorial approach. The material in each chapter is organized according to the complexity of the programs used as examples, starting with the simplest example and moving to more complex ones. Using Advanced MPI covers major changes in MPI-3, including changes to remote memory access and one-sided communication that simplify semantics and enable better performance on modern hardware; new features such as nonblocking and neighborhood collectives for greater scalability on large systems; and minor updates to parallel I/O and dynamic processes. It also covers support for hybrid shared-memory/message-passing programming; MPI_Message, which aids in certain types of multithreaded programming; features that handle very large data; an interface that allows the programmer and the developer to access performance data; and a new binding of MPI to Fortran. |
| openmp book: Patterns for Parallel Programming Mattson, 2004 |
| openmp book: Introduction to High Performance Scientific Computing Victor Eijkhout, 2010 This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications. |
| openmp book: Fortran 2018 with Parallel Programming Subrata Ray, 2019-08-22 The programming language Fortran dates back to 1957 when a team of IBM engineers released the first Fortran Compiler. During the past 60 years, the language had been revised and updated several times to incorporate more features to enable writing clean and structured computer programs. The present version is Fortran 2018. Since the dawn of the computer era, there had been a constant demand for a “larger” and “faster” machine. To increase the speed there are three hurdles. The density of the active components on a VLSI chip cannot be increased indefinitely and with the increase of the density heat dissipation becomes a major problem. Finally, the speed of any signal cannot exceed the velocity of the light. However, by using several inexpensive processors in parallel coupled with specialized software and hardware, programmers can achieve computing speed similar to a supercomputer. This book can be used to learn the modern Fortran from the beginning and the technique of developing parallel programs using Fortran. It is for anyone who wants to learn Fortran. Knowledge beyond high school mathematics is not required. There is not another book on the market yet which deals with Fortran 2018 as well as parallel programming. FEATURES Descriptions of majority of Fortran 2018 instructions Numerical Model String with Variable Length IEEE Arithmetic and Exceptions Dynamic Memory Management Pointers Bit handling C-Fortran Interoperability Object Oriented Programming Parallel Programming using Coarray Parallel Programming using OpenMP Parallel Programming using Message Passing Interface (MPI) THE AUTHOR Dr Subrata Ray, is a retired Professor, Indian Association for the Cultivation of Science, Kolkata. |
| openmp book: PVM Al Geist, 1994 Mathematics of Computing -- Parallelism. |
| openmp book: Shared Memory Multiprocessing Norihisa Suzuki, 1992 Shared memory multiprocessors are becoming the dominant architecture for small-scale parallel computation. This book is the first to provide a coherent review of current research in shared memory multiprocessing in the United States and Japan. It focuses particularly on scalable architecture that will be able to support hundreds of microprocessors as well as on efficient and economical ways of connecting these fast microprocessors. The 20 contributions are divided into sections covering the experience to date with multiprocessors, cache coherency, software systems, and examples of scalable shared memory multiprocessors. |
| openmp book: What Do We Know About the World? Gabrijela Kišiček, Igor Ž. Žagar, 2013-10-03 What do we know about the world? Rhetorical and Argumentative Perspectives is a book trying to answer the title question by contributing to rhetorical and argumentative studies. It consists of papers presented at the “First International Conference on Rhetoric in Croatia: the Days of Ivo Škarić” in May, 2012, and subsequently revised for publication. Through a variety of different routs, the papers explore the role of rhetoric and argumentation in various types of public discourse and present interdisciplinary work connecting linguists, phoneticians, philosophers, law experts and communication scientists in the common ground of rhetoric and argumentation.. The Conference was organized with the intent of paying respect to the Croatian rhetorician and professor emeritus Ivo Škarić who was the first to introduce rhetoric at the Department of Phonetics at the Faculty of Humanities and Social Sciences, University of Zagreb. |
| openmp book: Techniques for Optimizing Applications Rajat P. Garg, Ilya A. Sharapov, 2002 Software -- Programming Techniques. |
| openmp book: A Practical Programming Model for the Multi-Core Era Barbara Chapman, Weimin Zheng, Guang R. Gao, Mitsuhisa Sato, Eduard Ayguadé, Dongsheng Wang, 2008-06-11 This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on OpenMP, IWOMP 2007, held in Beijing, China, in June 2007. The 14 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 28 submissions. The papers address all topics related to OpenMP, such as OpenMP performance analysis and modeling, OpenMP performance and correctness tools and proposed OpenMP extensions, as well as applications in various domains, e.g., scientific computation, video games, computer graphics, multimedia, information retrieval, optimization, text processing, data mining, finance, signal and image processing, and numerical solvers. |
| openmp book: Programming Massively Parallel Processors David Kirk, Wen-mei Hwu, 2021 |
| openmp book: Parallel Programming Thomas Rauber, Gudula Rünger, 2013-06-13 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 standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years. |
| openmp book: Algorithms and Parallel Computing Fayez Gebali, 2011-04-19 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. |
| openmp book: Surrogates Robert B. Gramacy, 2020-03-10 Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for the analysis of computer simulation experiments. This book presents an applied introduction to GP regression for modelling and optimization of computer simulation experiments. Features: • Emphasis on methods, applications, and reproducibility. • R code is integrated throughout for application of the methods. • Includes more than 200 full colour figures. • Includes many exercises to supplement understanding, with separate solutions available from the author. • Supported by a website with full code available to reproduce all methods and examples. The book is primarily designed as a textbook for postgraduate students studying GP regression from mathematics, statistics, computer science, and engineering. Given the breadth of examples, it could also be used by researchers from these fields, as well as from economics, life science, social science, etc. |
| openmp book: Parallel Scientific Computing in C++ and MPI George Em Karniadakis, Robert M. Kirby II, 2003-06-16 Numerical algorithms, modern programming techniques, and parallel computing are often taught serially across different courses and different textbooks. The need to integrate concepts and tools usually comes only in employment or in research - after the courses are concluded - forcing the student to synthesise what is perceived to be three independent subfields into one. This book provides a seamless approach to stimulate the student simultaneously through the eyes of multiple disciplines, leading to enhanced understanding of scientific computing as a whole. The book includes both basic as well as advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Some of the advanced topics include wavelets, high-order methods, non-symmetric systems, and parallelization of sparse systems. The material covered is suited to students from engineering, computer science, physics and mathematics. |
| openmp book: Multicore DSP Naim Dahnoun, 2017-11-30 The only book to offer special coverage of the fundamentals of multicore DSP for implementation on the TMS320C66xx SoC This unique book provides readers with an understanding of the TMS320C66xx SoC as well as its constraints. It offers critical analysis of each element, which not only broadens their knowledge of the subject, but aids them in gaining a better understanding of how these elements work so well together. Written by Texas Instruments’ First DSP Educator Award winner, Naim Dahnoun, the book teaches readers how to use the development tools, take advantage of the maximum performance and functionality of this processor and have an understanding of the rich content which spans from architecture, development tools and programming models, such as OpenCL and OpenMP, to debugging tools. It also covers various multicore audio and image applications in detail. Additionally, this one-of-a-kind book is supplemented with: A rich set of tested laboratory exercises and solutions Audio and Image processing applications source code for the Code Composer Studio (integrated development environment from Texas Instruments) Multiple tables and illustrations With no other book on the market offering any coverage at all on the subject and its rich content with twenty chapters, Multicore DSP: From Algorithms to Real-time Implementation on the TMS320C66x SoC is a rare and much-needed source of information for undergraduates and postgraduates in the field that allows them to make real-time applications work in a relatively short period of time. It is also incredibly beneficial to hardware and software engineers involved in programming real-time embedded systems. |
| openmp book: Shared Memory Application Programming Victor Alessandrini, 2015-11-06 Shared Memory Application Programming presents the key concepts and applications of parallel programming, in an accessible and engaging style applicable to developers across many domains. Multithreaded programming is today a core technology, at the basis of all software development projects in any branch of applied computer science. This book guides readers to develop insights about threaded programming and introduces two popular platforms for multicore development: OpenMP and Intel Threading Building Blocks (TBB). Author Victor Alessandrini leverages his rich experience to explain each platform's design strategies, analyzing the focus and strengths underlying their often complementary capabilities, as well as their interoperability. The book is divided into two parts: the first develops the essential concepts of thread management and synchronization, discussing the way they are implemented in native multithreading libraries (Windows threads, Pthreads) as well as in the modern C++11 threads standard. The second provides an in-depth discussion of TBB and OpenMP including the latest features in OpenMP 4.0 extensions to ensure readers' skills are fully up to date. Focus progressively shifts from traditional thread parallelism to modern task parallelism deployed by modern programming environments. Several chapter include examples drawn from a variety of disciplines, including molecular dynamics and image processing, with full source code and a software library incorporating a number of utilities that readers can adapt into their own projects. - Designed to introduce threading and multicore programming to teach modern coding strategies for developers in applied computing - Leverages author Victor Alessandrini's rich experience to explain each platform's design strategies, analyzing the focus and strengths underlying their often complementary capabilities, as well as their interoperability - Includes complete, up-to-date discussions of OpenMP 4.0 and TBB - Based on the author's training sessions, including information on source code and software libraries which can be repurposed |
| openmp book: The Art of R Programming Norman Matloff, 2011-10-11 R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: –Create artful graphs to visualize complex data sets and functions –Write more efficient code using parallel R and vectorization –Interface R with C/C++ and Python for increased speed or functionality –Find new R packages for text analysis, image manipulation, and more –Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing. |
| openmp book: Elements of Parallel Computing Eric Aubanel, 2016-12-08 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 not from the point of view of hardware, but from a more abstract view of algorithmic and implementation patterns. The aim is to facilitate the teaching of parallel programming by surveying some key algorithmic structures and programming models, together with an abstract representation of the underlying hardware. The presentation is friendly and informal. The content of the book is language neutral, using pseudocode that represents common programming language models. The first five chapters present core concepts in parallel computing. SIMD, shared memory, and distributed memory machine models are covered, along with a brief discussion of what their execution models look like. The book also discusses decomposition as a fundamental activity in parallel algorithmic design, starting with a naive example, and continuing with a discussion of some key algorithmic structures. Important programming models are presented in depth, as well as important concepts of performance analysis, including work-depth analysis of task graphs, communication analysis of distributed memory algorithms, key performance metrics, and a discussion of barriers to obtaining good performance. The second part of the book presents three case studies that reinforce the concepts of the earlier chapters. One feature of these chapters is to contrast different solutions to the same problem, using select problems that aren't discussed frequently in parallel computing textbooks. They include the Single Source Shortest Path Problem, the Eikonal equation, and a classical computational geometry problem: computation of the two-dimensional convex hull. After presenting the problem and sequential algorithms, each chapter first discusses the sources of parallelism then surveys parallel algorithms. |
| openmp book: Modern Fortran Milan Curcic, 2020-10-07 Modern Fortran teaches you to develop fast, efficient parallel applications using twenty-first-century Fortran. In this guide, you’ll dive into Fortran by creating fun apps, including a tsunami simulator and a stock price analyzer. Filled with real-world use cases, insightful illustrations, and hands-on exercises, Modern Fortran helps you see this classic language in a whole new light. Summary Using Fortran, early and accurate forecasts for hurricanes and other major storms have saved thousands of lives. Better designs for ships, planes, and automobiles have made travel safer, more efficient, and less expensive than ever before. Using Fortran, low-level machine learning and deep learning libraries provide incredibly easy, fast, and insightful analysis of massive data. Fortran is an amazingly powerful and flexible programming language that forms the foundation of high performance computing for research, science, and industry. And it's come a long, long way since starting life on IBM mainframes in 1956. Modern Fortran is natively parallel, so it's uniquely suited for efficiently handling problems like complex simulations, long-range predictions, and ultra-precise designs. If you're working on tasks where speed, accuracy, and efficiency matter, it's time to discover—or re-discover—Fortran.. About the technology For over 60 years Fortran has been powering mission-critical scientific applications, and it isn't slowing down yet! Rock-solid reliability and new support for parallel programming make Fortran an essential language for next-generation high-performance computing. Simply put, the future is in parallel, and Fortran is already there. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the book Modern Fortran teaches you to develop fast, efficient parallel applications using twenty-first-century Fortran. In this guide, you'll dive into Fortran by creating fun apps, including a tsunami simulator and a stock price analyzer. Filled with real-world use cases, insightful illustrations, and hands-on exercises, Modern Fortran helps you see this classic language in a whole new light. What's inside Fortran's place in the modern world Working with variables, arrays, and functions Module development Parallelism with coarrays, teams, and events Interoperating Fortran with C About the reader For developers and computational scientists. No experience with Fortran required. About the author Milan Curcic is a meteorologist, oceanographer, and author of several general-purpose Fortran libraries and applications. Table of Contents PART 1 - GETTING STARTED WITH MODERN FORTRAN 1 Introducing Fortran 2 Getting started: Minimal working app PART 2 - CORE ELEMENTS OF FORTRAN 3 Writing reusable code with functions and subroutines 4 Organizing your Fortran code using modules 5 Analyzing time series data with arrays 6 Reading, writing, and formatting your data PART 3 - ADVANCED FORTRAN USE 7 Going parallel with Fortan coarrays 8 Working with abstract data using derived types 9 Generic procedures and operators for any data type 10 User-defined operators for derived types PART 4 - THE FINAL STRETCH 11 Interoperability with C: Exposing your app to the web 12 Advanced parallelism with teams, events, and collectives |
| openmp book: Data Parallel C++ James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian, 2020-11-19 Learn how to accelerate C++ programs using data parallelism. This open access book enables C++ programmers to be at the forefront of this exciting and important new development that is helping to push computing to new levels. It is full of practical advice, detailed explanations, and code examples to illustrate key topics. Data parallelism in C++ enables access to parallel resources in a modern heterogeneous system, freeing you from being locked into any particular computing device. Now a single C++ application can use any combination of devices—including GPUs, CPUs, FPGAs and AI ASICs—that are suitable to the problems at hand. This book begins by introducing data parallelism and foundational topics for effective use of the SYCL standard from the Khronos Group and Data Parallel C++ (DPC++), the open source compiler used in this book. Later chapters cover advanced topics including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. Data Parallel C++ provides you with everything needed to use SYCL for programming heterogeneous systems. What You'll Learn Accelerate C++ programs using data-parallel programming Target multiple device types (e.g. CPU, GPU, FPGA) Use SYCL and SYCL compilers Connect with computing’s heterogeneous future via Intel’s oneAPI initiative Who This Book Is For Those new data-parallel programming and computer programmers interested in data-parallel programming using C++. |
| openmp book: Understanding Latin American Politics Gregory Weeks, 2015 This textbook integrates domestic and international factors for understanding Latin American politics. The thematic structure of the book is to utilize three different levels of analysis to explain Latin American politics: international, national, and local. This approach has the benefit of incorporating the dynamics of globalization while also including political factors more at ground level, including the influence of subaltern groups. Although there may be important international influences on domestic politics, they interact with and are mediated by national political figures and grassroots activists. The book has four sections: Theoretical and Historical Background; Mexico, Central America, and the Caribbean; The Andean Region and Venezuela; and Brazil and the Southern Cone. Each chapter contains key terms, discussion questions, and further sources and a range of pedagogical materials for use in the classroom. This textbook is available in an open access digital edition. |
| openmp book: Introduction to Robotics Phillip McKerrow, 1991 This book provides an introductory text for students coming new to the field of robotics, and a survey of the state of the art for professional practitioners. Some of the outstanding features of this book include: . A unique approach which ties the multi-disciplinary components of robotics into a unified text. . Broad and in-depth coverage of all the major topics from the mechanics of movement to modelling and programming. . Rigorous mathematical treatment of mature topics combined with an algorithmic approach to newer areas of research. . Practical examples taken from a wide range of fields including computer science electronic engineering, mechanical engineering and production engineering. . Step-by-step development of problems and many worked examples. |
| openmp book: Computer Programming with COMIT II Victor H. Yngve, 1972 COMIT is a symbol-manipulating (or string-processing) language designed to handle texts, words, characters, logical expressions, descriptors, attributes, tags, and the like, and to manipulate them in the computer in ways that are relevant to problems in a variety of fields. COMIT is a general-purpose language which has been most efficiently used for problems in linguistics, mechanical translation of languages, information retrieval, modeling of cognitive processes, theorem proving, game playing, content analysis, graph theory, and many other primarily nonnumerical problems. In addition, COMIT serves as an introduction to a whole class of programming languages and language design features. This book is derived from two older manuals that have been out of print for some time, An Introduction to COMIT Programmingand COMIT Programmers' Reference Manual(MIT Press 1962). The programs originally run under COMIT will still run under COMIT II; yet this new publication includes improvements in the language that allow easier programming plus additional facilities. COMIT II is designed to be easily learned and used both as a language for a first course in programming for students in a wide range of disciplines and as a second or third programming language for more advanced students who can use this book for self-study. Included are numerous exercises and problems along with answers, as well as problems to be run on the computer under a problem-grader program that may be obtained from the author. COMIT II is fully available on the IBM 7000 series of computers, including the 709, 7090, 7040, and 7044, and a more recent implementation is available for the IBM 360. |
| openmp book: Introduction to Parallel Computing Roman Trobec, Boštjan Slivnik, Patricio Bulić, Borut Robič, 2018 Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms. This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters. Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs' run-times, and by engineering analysis of obtained results for improved parallel execution performances. Many examples and exercises support the exposition. |
| openmp book: The OpenMP Common Core Timothy G. Mattson, Yun (Helen) He, Alice E. Koniges, 2019-11-26 How to become a parallel programmer by learning the twenty-one essential components of OpenMP. This book guides readers through the most essential elements of OpenMP—the twenty-one components that most OpenMP programmers use most of the time, known collectively as the “OpenMP Common Core.” Once they have mastered these components, readers with no prior experience writing parallel code will be effective parallel programmers, ready to take on more complex aspects of OpenMP. The authors, drawing on twenty years of experience in teaching OpenMP, introduce material in discrete chunks ordered to support effective learning. OpenMP was created in 1997 to make it as simple as possible for applications programmers to write parallel code; since then, it has grown into a huge and complex system. The OpenMP Common Core goes back to basics, capturing the inherent simplicity of OpenMP. After introducing the fundamental concepts of parallel computing and history of OpenMP's development, the book covers topics including the core design pattern of parallel computing, the parallel and worksharing-loop constructs, the OpenMP data environment, and tasks. Two chapters on the OpenMP memory model are uniquely valuable for their pedagogic approach. The key for readers is to work through the material, use an OpenMP-enabled compiler, and write programs to experiment with each OpenMP directive or API routine as it is introduced. The book's website, updated continuously, offers a wide assortment of programs and exercises. |
OMP_NESTED deprecation - OpenMP® Forum
Jan 10, 2018 · OpenMP 5.0 will be the next version of the OpenMP specification, which we expect will be officially released in 2018. This technical report is an up-to-date draft of the 5.0 specs …
C/C++ min/max reduction with _Bool/bool - OpenMP® Forum
Sep 14, 2012 · The OpenMP 3.1 API spec states on p. 104, l. 1, that the private copy of a list item in a reduction clause is initialized as follows for min and max operators: Code: Select all max …
Reduction for arrays - OpenMP® Forum
Aug 14, 2008 · The usual methods of handling variables that can be accessed by multiple threads are the reduction clause, atomic, critical, and locks. If the variable is an array, then the …
OMP_SET_NUM_THREADS() - OpenMP® Forum
Dec 15, 2008 · OpenMP® Forum. Discussion on the OpenMP specification run by the OpenMP ARB. OpenMP and the OpenMP logo ...
macOS Big Sur - OpenMP® Forum
Dec 30, 2020 · OpenMP has no control over vendor's releases, so I'm afraid this is entirely down to Apple! As far as I know the situation for Big Sur has not changed from other recent MacOS …
Makefile : problems using -fopenmp - OpenMP® Forum
Jun 11, 2013 · OpenMP® Forum. Discussion on the OpenMP specification run by the OpenMP ARB. OpenMP and the OpenMP logo ...
shared array and volatile in Fortran - OpenMP® Forum
Mar 28, 2012 · Well, the "volatile" special behavior, I think it is language- and OpenMP version implementation- dependent. More specifically, Spec 2.5 defines (copied, p. 12): The volatile …
OMP_NESTED deprecation - OpenMP® Forum
Jan 10, 2018 · OpenMP 5.0 will be the next version of the OpenMP specification, which we expect will be officially released in 2018. This technical report is an up-to-date draft of the 5.0 specs …
C/C++ min/max reduction with _Bool/bool - OpenMP® Forum
Sep 14, 2012 · The OpenMP 3.1 API spec states on p. 104, l. 1, that the private copy of a list item in a reduction clause is initialized as follows for min and max operators: Code: Select all max …
Reduction for arrays - OpenMP® Forum
Aug 14, 2008 · The usual methods of handling variables that can be accessed by multiple threads are the reduction clause, atomic, critical, and locks. If the variable is an array, then the …
OMP_SET_NUM_THREADS() - OpenMP® Forum
Dec 15, 2008 · OpenMP® Forum. Discussion on the OpenMP specification run by the OpenMP ARB. OpenMP and the OpenMP logo ...
macOS Big Sur - OpenMP® Forum
Dec 30, 2020 · OpenMP has no control over vendor's releases, so I'm afraid this is entirely down to Apple! As far as I know the situation for Big Sur has not changed from other recent MacOS …
Makefile : problems using -fopenmp - OpenMP® Forum
Jun 11, 2013 · OpenMP® Forum. Discussion on the OpenMP specification run by the OpenMP ARB. OpenMP and the OpenMP logo ...
shared array and volatile in Fortran - OpenMP® Forum
Mar 28, 2012 · Well, the "volatile" special behavior, I think it is language- and OpenMP version implementation- dependent. More specifically, Spec 2.5 defines (copied, p. 12): The volatile …
