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Parallel Programming With Openacc


Parallel Programming With Openacc
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Parallel Programming With Openacc


Parallel Programming With Openacc
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Author : Rob Farber
language : en
Publisher: Newnes
Release Date : 2016-10-14

Parallel Programming With Openacc written by Rob Farber and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-14 with Computers categories.


Parallel Programming with OpenACC is a modern, practical guide to implementing dependable computing systems. The book explains how anyone can use OpenACC to quickly ramp-up application performance using high-level code directives called pragmas. The OpenACC directive-based programming model is designed to provide a simple, yet powerful, approach to accelerators without significant programming effort. Author Rob Farber, working with a team of expert contributors, demonstrates how to turn existing applications into portable GPU accelerated programs that demonstrate immediate speedups. The book also helps users get the most from the latest NVIDIA and AMD GPU plus multicore CPU architectures (and soon for Intel® Xeon PhiTM as well). Downloadable example codes provide hands-on OpenACC experience for common problems in scientific, commercial, big-data, and real-time systems. Topics include writing reusable code, asynchronous capabilities, using libraries, multicore clusters, and much more. Each chapter explains how a specific aspect of OpenACC technology fits, how it works, and the pitfalls to avoid. Throughout, the book demonstrates how the use of simple working examples that can be adapted to solve application needs. Presents the simplest way to leverage GPUs to achieve application speedups Shows how OpenACC works, including working examples that can be adapted for application needs Allows readers to download source code and slides from the book's companion web page



Openacc For Programmers


Openacc For Programmers
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Author : Sunita Chandrasekaran
language : en
Publisher: Addison-Wesley Professional
Release Date : 2017-09-11

Openacc For Programmers written by Sunita Chandrasekaran and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-11 with Computers categories.


The Complete Guide to OpenACC for Massively Parallel Programming Scientists and technical professionals can use OpenACC to leverage the immense power of modern GPUs without the complexity traditionally associated with programming them. OpenACCTM for Programmers is one of the first comprehensive and practical overviews of OpenACC for massively parallel programming. This book integrates contributions from 19 leading parallel-programming experts from academia, public research organizations, and industry. The authors and editors explain each key concept behind OpenACC, demonstrate how to use essential OpenACC development tools, and thoroughly explore each OpenACC feature set. Throughout, you’ll find realistic examples, hands-on exercises, and case studies showcasing the efficient use of OpenACC language constructs. You’ll discover how OpenACC’s language constructs can be translated to maximize application performance, and how its standard interface can target multiple platforms via widely used programming languages. Each chapter builds on what you’ve already learned, helping you build practical mastery one step at a time, whether you’re a GPU programmer, scientist, engineer, or student. All example code and exercise solutions are available for download at GitHub. Discover how OpenACC makes scalable parallel programming easier and more practical Walk through the OpenACC spec and learn how OpenACC directive syntax is structured Get productive with OpenACC code editors, compilers, debuggers, and performance analysis tools Build your first real-world OpenACC programs Exploit loop-level parallelism in OpenACC, understand the levels of parallelism available, and maximize accuracy or performance Learn how OpenACC programs are compiled Master OpenACC programming best practices Overcome common performance, portability, and interoperability challenges Efficiently distribute tasks across multiple processors Register your product at informit.com/register for convenient access to downloads, updates, and/or corrections as they become available.



Parallel Programming With Openacc


Parallel Programming With Openacc
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Author : Rob Farber
language : en
Publisher:
Release Date : 2017

Parallel Programming With Openacc written by Rob Farber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Parallel programming (Computer science) categories.


Parallel Programming with OpenACC is a modern, practical guide to implementing dependable computing systems. The book explains how anyone can use OpenACC to quickly ramp-up application performance using high-level code directives called pragmas. The OpenACC directive-based programming model is designed to provide a simple, yet powerful, approach to accelerators without significant programming effort. Author Rob Farber, working with a team of expert contributors, demonstrates how to turn existing applications into portable GPU accelerated programs that demonstrate immediate speedups. The book also helps users get the most from the latest NVIDIA and AMD GPU plus multicore CPU architectures (and soon for Intel® Xeon PhiTM as well). Downloadable example codes provide hands-on OpenACC experience for common problems in scientific, commercial, big-data, and real-time systems. Topics include writing reusable code, asynchronous capabilities, using libraries, multicore clusters, and much more. Each chapter explains how a specific aspect of OpenACC technology fits, how it works, and the pitfalls to avoid. Throughout, the book demonstrates how the use of simple working examples that can be adapted to solve application needs. Presents the simplest way to leverage GPUs to achieve application speedups Shows how OpenACC works, including working examples that can be adapted for application needs Allows readers to download source code and slides from the book's companion web page



Parallel Programming For Modern High Performance Computing Systems


Parallel Programming For Modern High Performance Computing Systems
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Author : Pawel Czarnul
language : en
Publisher: CRC Press
Release Date : 2018-03-05

Parallel Programming For Modern High Performance Computing Systems written by Pawel Czarnul and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-05 with Business & Economics categories.


In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs



Cuda Programming


Cuda Programming
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Author : Shane Cook
language : en
Publisher: Morgan Kaufmann
Release Date : 2017-10-01

Cuda Programming written by Shane Cook and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-01 with Computers categories.


CUDA Programming: A Developer's Guide to Parallel Computing with GPUs, Second Edition is a fully revised, updated, practical guide that provides a solid foundation for developers learning parallel programming with CUDA. This guide iincludes updates that cover both the Kepler and Maxwell GPUs from NVIDIA, as well as the latest heterogeneous systems from AMD. Suitable for someone without a parallel programming background or previous CUDA experience, as well as those who already have dabbled in GPU programming, the contents range from installation and getting started, to building your own GPU workstation. This revision includes a new chapter on visualizing data, and new content on the latest CUDA features including data caching, shared memory, and dynamic parallelism. Author Shane Cook also covers the latest host systems and changes to the installation process, NVIDIA’s Parallel NSight IDE, and hardware systems that run CUDA applications. The final new chapter looks ahead to future GPU platforms and releases including on-core ARM CPU and NVlink technologies. Provides a solid foundation in how to program GPUs using in CUDA Discusses multiple options such as libraries, OpenCL, OpenACC and other programming languages Explains how to design and optimize code for several generations of GPUs and platforms Covers the latest debugging and profiling tools



Accelerator Programming Using Directives


Accelerator Programming Using Directives
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Author : Sunita Chandrasekaran
language : en
Publisher: Springer
Release Date : 2018-02-09

Accelerator Programming Using Directives written by Sunita Chandrasekaran and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-09 with Computers categories.


This book constitutes the refereed post-conference proceedings of the 4th International Workshop on Accelerator Programming Using Directives, WACCPD 2017, held in Denver, CO, USA, in November 2017. The 9 full papers presented have been carefully reviewed and selected from 14 submissions. The papers share knowledge and experiences to program emerging complex parallel computing systems. They are organized in the following three sections: applications; environments; and program evaluation.



Parallel And High Performance Computing


Parallel And High Performance Computing
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Author : Robert Robey
language : en
Publisher: Simon and Schuster
Release Date : 2021-08-24

Parallel And High Performance Computing written by Robert Robey and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-24 with Computers categories.


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



Programming Massively Parallel Processors


Programming Massively Parallel Processors
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Author : David B. Kirk
language : en
Publisher: Newnes
Release Date : 2012-12-31

Programming Massively Parallel Processors written by David B. Kirk and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-31 with Computers categories.


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



Euro Par 2012 Parallel Processing


Euro Par 2012 Parallel Processing
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Author : Christos Kaklamanis
language : en
Publisher: Springer
Release Date : 2012-07-26

Euro Par 2012 Parallel Processing written by Christos Kaklamanis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-26 with Computers categories.


This book constitutes the thoroughly refereed proceedings of the 18th International Conference, Euro-Par 2012, held in Rhodes Islands, Greece, in August 2012. The 75 revised full papers presented were carefully reviewed and selected from 228 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load balancing; high-performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; peer to peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance network and communication; mobile and ubiquitous computing; high performance and scientific applications; GPU and accelerators computing.



Programming Massively Parallel Processors


Programming Massively Parallel Processors
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Author : David B. Kirk
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-11-24

Programming Massively Parallel Processors written by David B. Kirk and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-24 with Computers categories.


Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing Utilizes CUDA version 7.5, NVIDIA's software development tool created specifically for massively parallel environments Contains new and updated case studies Includes coverage of newer libraries, such as CuDNN for Deep Learning