12 products were found matching your search for OpenMP in 1 shops:

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.

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.

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.

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.

Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

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 openmp addresses 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.

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 OpenMP addresses 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 todays parallel platforms. . .

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 OpenMP addresses 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 todays parallel platforms. . .

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 CUDADemonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performanceParticular focus on the emerging area of divisible load theory and its impact on load balancing and distributed systemsDownload source code, examples, and instructor support materials on the book's companion website

An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP. As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs. In edition, this new edition includes coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach student how to compile, run and modify example programs.Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examplesFocuses on designing, debugging and evaluating the performance of distributed and shared-memory programsExplains how to develop parallel programs using MPI, Pthreads and OpenMP programming modelsIncludes a robust package of online ancillaries for instructors and studentsProvides lecture slides, a solutions manual, downloadable source code and an image bank

An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP. As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs. In edition, this new edition includes coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach student how to compile, run and modify example programs.Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examplesFocuses on designing, debugging and evaluating the performance of distributed and shared-memory programsExplains how to develop parallel programs using MPI, Pthreads and OpenMP programming modelsIncludes a robust package of online ancillaries for instructors and studentsProvides lecture slides, a solutions manual, downloadable source code and an image bank

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 CUDADemonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performanceParticular focus on the emerging area of divisible load theory and its impact on load balancing and distributed systemsDownload source code, examples, and instructor support materials on the book's companion website