multicore and gpu programming

Multicore And GPU Programming
Author: Gerassimos Barlas
Publisher: Elsevier
Release Date: 2014-12-16
Pages: 698
ISBN:
Available Language: English, Spanish, And French
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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

The OpenCL Programming Book
Author: http://www.fixstars.com/en/opencl/book/
Publisher: Fixstars
Release Date:
Pages:
ISBN:
Available Language: English, Spanish, And French
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Exam Prep For  Multicore And Gpu Programming  An Integrated
Author:
Publisher:
Release Date:
Pages:
ISBN:
Available Language: English, Spanish, And French
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Parallel Programming
Author: Thomas Rauber
Publisher: Springer Science & Business Media
Release Date: 2013-06-13
Pages: 516
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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.

GPU Programming In MATLAB
Author: Nikolaos Ploskas
Publisher: Morgan Kaufmann
Release Date: 2016-08-25
Pages: 318
ISBN:
Available Language: English, Spanish, And French
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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

Multicore Computing
Author: Sanguthevar Rajasekaran
Publisher: CRC Press
Release Date: 2013-12-12
Pages: 452
ISBN:
Available Language: English, Spanish, And French
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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.

Programming Multicore And Many Core Computing Systems
Author: Sabri Pllana
Publisher: John Wiley & Sons
Release Date: 2017-01-23
Pages: 528
ISBN:
Available Language: English, Spanish, And French
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Programming multi-core and many-core computing systems Sabri Pllana, Linnaeus University, Sweden Fatos Xhafa, Technical University of Catalonia, Spain Provides state-of-the-art methods for programming multi-core and many-core systems The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems. Program development for multi-core processors, especially for heterogeneous multi-core processors, is significantly more complex than for single-core processors. However, programmers have been traditionally trained for the development of sequential programs, and only a small percentage of them have experience with parallel programming. In the past, only a relatively small group of programmers interested in High Performance Computing (HPC) was concerned with the parallel programming issues, but the situation has changed dramatically with the appearance of multi-core processors on commonly used computing systems. It is expected that with the pervasiveness of multi-core processors, parallel programming will become mainstream. The pervasiveness of multi-core processors affects a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This book assists programmers in mastering the efficient programming of multi-core systems, which is of paramount importance for the software-intensive industry towards a more effective product-development cycle. Key features: Lessons, challenges, and roadmaps ahead. Contains real world examples and case studies. Helps programmers in mastering the efficient programming of multi-core and many-core systems. The book serves as a reference for a larger audience of practitioners, young researchers and graduate level students. A basic level of programming knowledge is required to use this book.

Parallel Computing
Author: Barbara Chapman
Publisher: IOS Press
Release Date: 2010-01-01
Pages: 739
ISBN:
Available Language: English, Spanish, And French
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Parallel computing technologies have brought dramatic changes to mainstream computing; the majority of today's PC's, laptops and even notebooks incorporate multiprocessor chips with up to four processors. Standard components are increasingly combined with GPU's (Graphics Processing Unit), originally designed for high-speed graphics processing, and FPGA's (Free Programmable Gate Array) to build parallel computers with a wide spectrum of high-speed processing functions. The scale of this powerful hardware is limited only by factors such as energy consumption and thermal control However, in addition to hardware factors, the practical use of petascale and exascale machines is often hampered by the difficulty of developing software which will run effectively and efficiently on such architecture This book includes selected and refereed papers, presented at the 2009 international Parallel Computing conference (ParCo2009), which set out to address these problems. It provides a snapshot of the state-of-the-art of parallel computing technologies in hardware, application and software development Areas covered include: numerical algorithms, grid and cloud computing, programming - including GPU and cell programming. The book also includes papers presented at the six mini-symposia held at the conference

Facing The Multicore Challenge III
Author: Rainer Keller
Publisher: Springer
Release Date: 2013-01-11
Pages: 146
ISBN:
Available Language: English, Spanish, And French
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This state-of-the-art survey features topics related to the impact of multicore, manycore, and coprocessor technologies in science and large-scale applications in an interdisciplinary environment. The papers included in this survey cover research in mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, hardware-aware computing, heterogeneous platforms, manycore technologies, performance tuning, and requirements for large-scale applications. The contributions presented in this volume are an outcome of an inspiring conference conceived and organized by the editors at the University of Applied Sciences (HfT) in Stuttgart, Germany, in September 2012. The 10 revised full papers selected from 21 submissions are presented together with the twelve poster abstracts and focus on combination of new aspects of microprocessor technologies, parallel applications, numerical simulation, and software development; thus they clearly show the potential of emerging technologies in the area of multicore and manycore processors that are paving the way towards personal supercomputing and very likely towards exascale computing.

Computational Physics
Author: Rubin H. Landau
Publisher: John Wiley & Sons
Release Date: 2015-09-08
Pages: 644
ISBN:
Available Language: English, Spanish, And French
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The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language. Python has become very popular, particularly for physics education and large scientific projects. It is probably the easiest programming language to learn for beginners, yet is also used for mainstream scientific computing, and has packages for excellent graphics and even symbolic manipulations. The text is designed for an upper-level undergraduate or beginning graduate course and provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. As part of the teaching of using computers to solve scientific problems, the reader is encouraged to work through a sample problem stated at the beginning of each chapter or unit, which involves studying the text, writing, debugging and running programs, visualizing the results, and the expressing in words what has been done and what can be concluded. Then there are exercises and problems at the end of each chapter for the reader to work on their own (with model programs given for that purpose). The text could be used for a one-semester course on scientific computing. The relevant topics for that are covered in the first third of the book. The latter two-thirds of the text includes more physics and can be used for a two-semester course in computational physics, covering nonlinear ODEs, Chaotic Scattering, Fourier Analysis, Wavelet Analysis, Nonlinear Maps, Chaotic systems, Fractals and Parallel Computing. The e-book extends the paper version by including many codes, visualizations and applets, as well as links to video lectures. * A table at the beginning of each chapter indicates video lectures, slides, applets and animations. * Applets illustrate the results to be expected for projects in the book, and to help understand some abstract concepts (e.g. Chaotic Scattering) * The eBook's figures, equations, sections, chapters, index, table of contents, code listings, glossary, animations and executable codes (both Applets and Python programs) are linked, much like in a Web document. * Some equations are linked to their xml forms (which can be imported into Maple or Mathematica for manipulation). * The e-book will link to video-based lecture modules, held by principal author Professor Rubin Landau, that cover most every topic in the book.

Parallel Programming With OpenACC
Author: Rob Farber
Publisher: Newnes
Release Date: 2016-10-14
Pages: 326
ISBN:
Available Language: English, Spanish, And French
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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

Using MPI
Author: William Gropp
Publisher: MIT Press
Release Date: 2014-11-07
Pages: 336
ISBN:
Available Language: English, Spanish, And French
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This book offers a thoroughly updated guide to the MPI (Message-Passing Interface) standard library for writing programs for parallel computers. Since the publication of the previous edition of Using MPI, parallel computing has become mainstream. Today, applications run on computers with millions of processors; multiple processors sharing memory and multicore processors with multiple hardware threads per core are common. The MPI-3 Forum recently brought the MPI standard up to date with respect to developments in hardware capabilities, core language evolution, the needs of applications, and experience gained over the years by vendors, implementers, and users. This third edition of Using MPI reflects these changes in both text and example code. The book takes an informal, tutorial approach, introducing each concept through easy-to-understand examples, including actual code in C and Fortran. Topics include using MPI in simple programs, virtual topologies, MPI datatypes, parallel libraries, and a comparison of MPI with sockets. For the third edition, example code has been brought up to date; applications have been updated; and references reflect the recent attention MPI has received in the literature. A companion volume, Using Advanced MPI, covers more advanced topics, including hybrid programming and coping with large data.

Languages And Compilers For Parallel Computing
Author: Sanjay Rajopadhye
Publisher: Springer
Release Date: 2013-01-18
Pages: 299
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2011, held in Fort Collins, CO, USA, in September 2011. The 19 revised full papers presented and 19 poster papers were carefully reviewed and selected from 52 submissions. The scope of the workshop spans the theoretical and practical aspects of parallel and high-performance computing, and targets parallel platforms including concurrent, multithreaded, multicore, accelerator, multiprocessor, and cluster systems.

Python Parallel Programming Cookbook
Author: Giancarlo Zaccone
Publisher: Packt Publishing Ltd
Release Date: 2015-08-26
Pages: 286
ISBN:
Available Language: English, Spanish, And French
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Master efficient parallel programming to build powerful applications using Python About This Book Design and implement efficient parallel software Master new programming techniques to address and solve complex programming problems Explore the world of parallel programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered in great depth Who This Book Is For Python Parallel Programming Cookbook is intended for software developers who are well versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing. What You Will Learn Synchronize multiple threads and processes to manage parallel tasks Implement message passing communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational tasks Write efficient programs by adopting the event-driven programming model Explore the cloud technology with DJango and Google App Engine Apply parallel programming techniques that can lead to performance improvements In Detail Parallel programming techniques are required for a developer to get the best use of all the computational resources available today and to build efficient software systems. From multi-core to GPU systems up to the distributed architectures, the high computation of programs throughout requires the use of programming tools and software libraries. Because of this, it is becoming increasingly important to know what the parallel programming techniques are. Python is commonly used as even non-experts can easily deal with its concepts. This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will also understand the StarCluster framework, Pycsp, Scoop, and Disco modules in Python. Further on, you will learn GPU programming with Python using the PyCUDA module along with evaluating performance limitations. Next you will get acquainted with the cloud computing concepts in Python, using Google App Engine (GAE), and building your first application with GAE. Lastly, you will learn about grid computing concepts in Python and using PyGlobus toolkit, GFTP and GASS COPY to transfer files, and service monitoring in PyGlobus. Style and approach A step-by-step guide to parallel programming using Python, with recipes accompanied by one or more programming examples. It is a practically oriented book and has all the necessary underlying parallel computing concepts.

Parallel And High Performance Computing
Author: Robert Robey
Publisher: Manning Publications
Release Date: 2021-04-27
Pages: 600
ISBN:
Available Language: English, Spanish, And French
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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. 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. Parallel and High Performance Computing is for anyone who needs to maximize application performance and reduce execution time. Get under the hood of parallel computing architecture and learn to evaluate hardware performance, scale up your resources to tackle larger problem sizes, and deliver a level of energy efficiency that makes high performance possible on hand-held devices. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Central European Functional Programming School
Author: Viktória Zsók
Publisher: Springer
Release Date: 2015-03-20
Pages: 507
ISBN:
Available Language: English, Spanish, And French
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This volume presents the revised lecture notes of selected talks given at the Fifth Central European Functional Programming School, CEFP 2013, held in July 2013 in Cluj-Napoca, Romania. The 14 revised full papers presented were carefully reviewed and selected. The lectures cover a wide range of distributed and multicore functional programming subjects. The last 5 papers are selected papers of the PhD Workshop organized for the participants of the summer school.

Optimization  Application  And Usability Of Algorithmic Skeletons For Parallel Programming On Multi Core And Multi GPU Clusters
Author: Fabian Wrede
Publisher:
Release Date: 2020
Pages:
ISBN:
Available Language: English, Spanish, And French
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Scientific Computing With Multicore And Accelerators
Author: Jakub Kurzak
Publisher: CRC Press
Release Date: 2010-12-07
Pages: 514
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The hybrid/heterogeneous nature of future microprocessors and large high-performance computing systems will result in a reliance on two major types of components: multicore/manycore central processing units and special purpose hardware/massively parallel accelerators. While these technologies have numerous benefits, they also pose substantial performance challenges for developers, including scalability, software tuning, and programming issues. Researchers at the Forefront Reveal Results from Their Own State-of-the-Art Work Edited by some of the top researchers in the field and with contributions from a variety of international experts, Scientific Computing with Multicore and Accelerators focuses on the architectural design and implementation of multicore and manycore processors and accelerators, including graphics processing units (GPUs) and the Sony Toshiba IBM (STI) Cell Broadband Engine (BE) currently used in the Sony PlayStation 3. The book explains how numerical libraries, such as LAPACK, help solve computational science problems; explores the emerging area of hardware-oriented numerics; and presents the design of a fast Fourier transform (FFT) and a parallel list ranking algorithm for the Cell BE. It covers stencil computations, auto-tuning, optimizations of a computational kernel, sequence alignment and homology, and pairwise computations. The book also evaluates the portability of drug design applications to the Cell BE and illustrates how to successfully exploit the computational capabilities of GPUs for scientific applications. It concludes with chapters on dataflow frameworks, the Charm++ programming model, scan algorithms, and a portable intracore communication framework. Explores the New Computational Landscape of Hybrid Processors By offering insight into the process of constructing and effectively using the technology, this volume provides a thorough and practical introduction to the area of hybrid computing. It discusses introductory concepts and simple examples of parallel computing, logical and performance debugging for parallel computing, and advanced topics and issues related to the use and building of many applications.

Facing The Multicore Challenge
Author: Rainer Keller
Publisher: Springer Science & Business Media
Release Date: 2010-10-06
Pages: 156
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This state-of-the-art survey features topics related to the impact of multicore and coprocessor technologies in science and for large-scale applications in an interdisciplinary environment. The papers cover all issues of current research in mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, compilers, hardware-aware computing, heterogeneous platforms, emerging architectures, tools, performance tuning, and requirements for large-scale applications. The contributions presented in this volume offer a survey on the state of the art, the concepts and perspectives for future developments. They are an outcome of an inspiring conference conceived and organized by the editors within the junior scientist program of Heidelberg Academy for Sciences and Humanities titled "Facing the Multicore-Challenge", held at Heidelberg, Germany, in March 2010. The 12 revised full papers presented together with the extended abstracts of 3 invited lectures focus on combination of new aspects of multicore microprocessor technologies, parallel applications, numerical simulation, software development, and tools; thus they clearly show the potential of emerging technologies in the area of multicore and manycore processors that are paving the way towards personal supercomputing.

Professional CUDA C Programming
Author: John Cheng
Publisher: John Wiley & Sons
Release Date: 2014-09-08
Pages: 528
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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.