Multicore And Gpu Programming

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Multicore and GPU Programming

Author : Gerassimos Barlas
Publisher : Morgan Kaufmann
ISBN 13 : 0128141212
Total Pages : 1026 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Multicore and GPU Programming by : Gerassimos Barlas

Download or read book Multicore and GPU Programming written by Gerassimos Barlas and published by Morgan Kaufmann. This book was released on 2022-02-09 with total page 1026 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multicore and GPU Programming: An Integrated Approach, Second Edition offers broad coverage of key parallel computing tools, essential for multi-core CPU programming and many-core "massively parallel" computing. Using threads, OpenMP, MPI, CUDA and other state-of-the-art tools, the book teaches the design and development of software capable of taking advantage of modern computing platforms that incorporate CPUs, GPUs and other accelerators. Presenting material refined over more than two decades of teaching parallel computing, author Gerassimos Barlas minimizes the challenge of transitioning from sequential programming to mastering parallel platforms with multiple examples, extensive case studies, and full source code. By using this book, readers will better understand how to 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 parallel machines. Includes comprehensive coverage of all major multi-core and many-core programming tools and platforms, including threads, OpenMP, MPI, CUDA, OpenCL and Thrust Covers the most recent versions of the above at the time of publication Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance Updates in the second edition include the use of the C++17 standard for all sample code, a new chapter on concurrent data structures, a new chapter on OpenCL, and the latest research on load balancing Includes downloadable source code, examples and instructor support materials on the book’s companion website

Multicore and GPU Programming

Author : Gerassimos Barlas
Publisher : Elsevier
ISBN 13 : 0124171400
Total Pages : 698 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Multicore and GPU Programming by : Gerassimos Barlas

Download or read book Multicore and GPU Programming written by Gerassimos Barlas and published by Elsevier. This book was released on 2014-12-16 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

GPU Programming in MATLAB

Author : Nikolaos Ploskas
Publisher : Morgan Kaufmann
ISBN 13 : 0128051337
Total Pages : 318 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis GPU Programming in MATLAB by : Nikolaos Ploskas

Download or read book GPU Programming in MATLAB written by Nikolaos Ploskas and published by Morgan Kaufmann. This book was released on 2016-08-25 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: GPU programming in MATLAB is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU programming. The next part covers built-in, GPU-enabled features of MATLAB, including options to leverage GPUs across multicore or different computer systems. Finally, advanced material includes CUDA code in MATLAB and optimizing existing GPU applications. Throughout the book, examples and source codes illustrate every concept so that readers can immediately apply them to their own development. Provides in-depth, comprehensive coverage of GPUs with MATLAB, including the parallel computing toolbox and built-in features for other MATLAB toolboxes Explains how to accelerate computationally heavy applications in MATLAB without the need to re-write them in another language Presents case studies illustrating key concepts across multiple fields Includes source code, sample datasets, and lecture slides

Hands-On GPU Programming with Python and CUDA

Author : Dr. Brian Tuomanen
Publisher : Packt Publishing Ltd
ISBN 13 : 1788995228
Total Pages : 300 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On GPU Programming with Python and CUDA by : Dr. Brian Tuomanen

Download or read book Hands-On GPU Programming with Python and CUDA written by Dr. Brian Tuomanen and published by Packt Publishing Ltd. This book was released on 2018-11-27 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book. Key FeaturesExpand your background in GPU programming—PyCUDA, scikit-cuda, and NsightEffectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolverApply GPU programming to modern data science applicationsBook Description Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory. As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS. With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain. By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing. What you will learnLaunch GPU code directly from PythonWrite effective and efficient GPU kernels and device functionsUse libraries such as cuFFT, cuBLAS, and cuSolverDebug and profile your code with Nsight and Visual ProfilerApply GPU programming to datascience problemsBuild a GPU-based deep neuralnetwork from scratchExplore advanced GPU hardware features, such as warp shufflingWho this book is for Hands-On GPU Programming with Python and CUDA is for developers and data scientists who want to learn the basics of effective GPU programming to improve performance using Python code. You should have an understanding of first-year college or university-level engineering mathematics and physics, and have some experience with Python as well as in any C-based programming language such as C, C++, Go, or Java.

The OpenCL Programming Book: parallel Programming for MultiCore CPU and GPU

Author :
Publisher : Fixstars
ISBN 13 :
Total Pages : 246 pages
Book Rating : 4./5 ( download)

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Book Synopsis The OpenCL Programming Book: parallel Programming for MultiCore CPU and GPU by :

Download or read book The OpenCL Programming Book: parallel Programming for MultiCore CPU and GPU written by and published by Fixstars. This book was released on with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Parallel Programming

Author : Thomas Rauber
Publisher : Springer Science & Business Media
ISBN 13 : 364204817X
Total Pages : 463 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Parallel Programming by : Thomas Rauber

Download or read book Parallel Programming written by Thomas Rauber and published by Springer Science & Business Media. This book was released on 2010-03-10 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. The main goal of the book is to present parallel programming techniques that can be used in many situations for many 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 presented material has been used for courses in parallel programming at different universities for many years.

CUDA Programming

Author : Shane Cook
Publisher : Newnes
ISBN 13 : 0124159338
Total Pages : 592 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis CUDA Programming by : Shane Cook

Download or read book CUDA Programming written by Shane Cook and published by Newnes. This book was released on 2012-11-13 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'CUDA Programming' offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation.

Programming Massively Parallel Processors

Author : David B. Kirk
Publisher : Newnes
ISBN 13 : 0123914183
Total Pages : 514 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Programming Massively Parallel Processors by : David B. Kirk

Download or read book Programming Massively Parallel Processors written by David B. Kirk and published by Newnes. This book was released on 2012-12-31 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

The CUDA Handbook

Author : Nicholas Wilt
Publisher : Addison-Wesley
ISBN 13 : 0133261506
Total Pages : 528 pages
Book Rating : 4.1/5 (332 download)

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Book Synopsis The CUDA Handbook by : Nicholas Wilt

Download or read book The CUDA Handbook written by Nicholas Wilt and published by Addison-Wesley. This book was released on 2013-06-11 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how the driver checks progress; more experienced CUDA developers will appreciate the expert coverage of topics such as the driver API and context migration, as well as the guidance on how best to structure CPU/GPU data interchange and synchronization. The accompanying open source code–more than 25,000 lines of it, freely available at www.cudahandbook.com–is specifically intended to be reused and repurposed by developers. Designed to be both a comprehensive reference and a practical cookbook, the text is divided into the following three parts: Part I, Overview, gives high-level descriptions of the hardware and software that make CUDA possible. Part II, Details, provides thorough descriptions of every aspect of CUDA, including Memory Streams and events Models of execution, including the dynamic parallelism feature, new with CUDA 5.0 and SM 3.5 The streaming multiprocessors, including descriptions of all features through SM 3.5 Programming multiple GPUs Texturing The source code accompanying Part II is presented as reusable microbenchmarks and microdemos, designed to expose specific hardware characteristics or highlight specific use cases. Part III, Select Applications, details specific families of CUDA applications and key parallel algorithms, including Streaming workloads Reduction Parallel prefix sum (Scan) N-body Image Processing These algorithms cover the full range of potential CUDA applications.

Parallel and Concurrent Programming in Haskell

Author : Simon Marlow
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449335926
Total Pages : 322 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Parallel and Concurrent Programming in Haskell by : Simon Marlow

Download or read book Parallel and Concurrent Programming in Haskell written by Simon Marlow and published by "O'Reilly Media, Inc.". This book was released on 2013-07-12 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network

Professional CUDA C Programming

Author : John Cheng
Publisher : John Wiley & Sons
ISBN 13 : 1118739329
Total Pages : 528 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Professional CUDA C Programming by : John Cheng

Download or read book Professional CUDA C Programming written by John Cheng and published by John Wiley & Sons. This book was released on 2014-09-09 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers to explore both the "hard" and "soft" aspects of GPU programming. Computing architectures are experiencing a fundamental shift toward scalable parallel computing motivated by application requirements in industry and science. This book demonstrates the challenges of efficiently utilizing compute resources at peak performance, presents modern techniques for tackling these challenges, while increasing accessibility for professionals who are not necessarily parallel programming experts. The CUDA programming model and tools empower developers to write high-performance applications on a scalable, parallel computing platform: the GPU. However, CUDA itself can be difficult to learn without extensive programming experience. Recognized CUDA authorities John Cheng, Max Grossman, and Ty McKercher guide readers through essential GPU programming skills and best practices in Professional CUDA C Programming, including: CUDA Programming Model GPU Execution Model GPU Memory model Streams, Event and Concurrency Multi-GPU Programming CUDA Domain-Specific Libraries Profiling and Performance Tuning The book makes complex CUDA concepts easy to understand for anyone with knowledge of basic software development with exercises designed to be both readable and high-performance. For the professional seeking entrance to parallel computing and the high-performance computing community, Professional CUDA C Programming is an invaluable resource, with the most current information available on the market.

Facing the Multicore-Challenge

Author : Rainer Keller
Publisher : Springer
ISBN 13 : 3642162339
Total Pages : 156 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Facing the Multicore-Challenge by : Rainer Keller

Download or read book Facing the Multicore-Challenge written by Rainer Keller and published by Springer. This book was released on 2010-10-05 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey of the impact of multicore and co-processor technologies on science as well as on large-scale interdisciplinary applications covers the state of the art in the field. It also points to a number of potentially fruitful areas for future research.

Parallel Programming

Author : Thomas Rauber
Publisher : Springer Science & Business Media
ISBN 13 : 3642378013
Total Pages : 523 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Parallel Programming by : Thomas Rauber

Download or read book Parallel Programming written by Thomas Rauber and published by Springer Science & Business Media. This book was released on 2013-06-13 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Parallel Programming

Author : Thomas Rauber
Publisher : Springer Nature
ISBN 13 : 3031289242
Total Pages : 563 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Parallel Programming by : Thomas Rauber

Download or read book Parallel Programming written by Thomas Rauber and published by Springer Nature. This book was released on 2023-05-06 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook covers the new development in processor architecture and parallel hardware. It provides 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. The 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. In particular, this third edition includes an extended update of the chapter on computer architecture and performance analysis taking new developments such as the aspect of energy consumption into consideration. The description of OpenMP has been extended and now also captures the task concept of OpenMP. The chapter on message-passing programming has been extended and updated to include new features of MPI such as extended reduction operations and non-blocking collective communication operations. The chapter on GPU programming also has been updated. All other chapters also have been revised carefully. The main goal of this book is to present parallel programming techniques that can be used in many situations for many application areas and to enable the reader to develop correct and efficient parallel programs. Many example programs and exercises are provided to support this goal and to show how the techniques can be applied to further applications. The book can be used as a textbook for students as well as a reference book for professionals. The material of the book has been used for courses in parallel programming at different universities for many years.

Multicore Computing

Author : Sanguthevar Rajasekaran
Publisher : CRC Press
ISBN 13 : 1439854351
Total Pages : 452 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Multicore Computing by : Sanguthevar Rajasekaran

Download or read book Multicore Computing written by Sanguthevar Rajasekaran and published by CRC Press. This book was released on 2013-12-12 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the advent of multicore architectures. However, programming multicore machines is much more difficult due to oddities existing in the architectures. Offering insights into different facets of this area, Multicore Computing: Algorithms, Architectures, and Applications focuses on the architectures, algorithms, and applications of multicore computing. It will help readers understand the intricacies of these architectures and prepare them to design efficient multicore algorithms. Contributors at the forefront of the field cover the memory hierarchy for multicore and manycore processors, the caching strategy Flexible Set Balancing, the main features of the latest SPARC architecture specification, the Cilk and Cilk++ programming languages, the numerical software library Parallel Linear Algebra Software for Multicore Architectures (PLASMA), and the exact multipattern string matching algorithm of Aho-Corasick. They also describe the architecture and programming model of the NVIDIA Tesla GPU, discuss scheduling directed acyclic graphs onto multi/manycore processors, and evaluate design trade-offs among Intel and AMD multicore processors, IBM Cell Broadband Engine, and NVIDIA GPUs. In addition, the book explains how to design algorithms for the Cell Broadband Engine and how to use the backprojection algorithm for generating images from synthetic aperture radar data.

CUDA by Example

Author : Jason Sanders
Publisher : Addison-Wesley Professional
ISBN 13 : 0132180138
Total Pages : 523 pages
Book Rating : 4.1/5 (321 download)

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Book Synopsis CUDA by Example by : Jason Sanders

Download or read book CUDA by Example written by Jason Sanders and published by Addison-Wesley Professional. This book was released on 2010-07-19 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html

Parallel and High Performance Computing

Author : Robert Robey
Publisher : Simon and Schuster
ISBN 13 : 1638350388
Total Pages : 702 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Parallel and High Performance Computing by : Robert Robey

Download or read book Parallel and High Performance Computing written by Robert Robey and published by Simon and Schuster. This book was released on 2021-08-24 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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