Multicore and GPU Programming

Book Multicore and GPU Programming Cover

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  • Publisher : Elsevier
  • Release : 16 December 2014
  • ISBN : 9780124171404
  • Page : 698 pages
  • Rating : 4.5/5 from 103 voters

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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

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Multicore and GPU Programming

Multicore and GPU Programming
  • Author : Gerassimos Barlas
  • Publisher : Elsevier
  • Release Date : 2014-12-16
  • ISBN : 9780124171404
GET THIS BOOKMulticore and GPU Programming

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

Multicore and GPU Programming

Multicore and GPU Programming
  • Author : Gerassimos Barlas
  • Publisher : Morgan Kaufmann
  • Release Date : 2022-05-05
  • ISBN : 9780128141212
GET THIS BOOKMulticore and GPU Programming

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

GPU Programming in MATLAB

GPU Programming in MATLAB
  • Author : Nikolaos Ploskas,Nikolaos Samaras
  • Publisher : Morgan Kaufmann
  • Release Date : 2016-08-25
  • ISBN : 9780128051337
GET THIS BOOKGPU Programming in MATLAB

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

Parallel Programming with OpenACC

Parallel Programming with OpenACC
  • Author : Rob Farber
  • Publisher : Newnes
  • Release Date : 2016-10-14
  • ISBN : 9780124104594
GET THIS BOOKParallel Programming with OpenACC

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

Hands-On GPU Programming with Python and CUDA

Hands-On GPU Programming with Python and CUDA
  • Author : Dr. Brian Tuomanen
  • Publisher : Packt Publishing Ltd
  • Release Date : 2018-11-27
  • ISBN : 9781788995221
GET THIS BOOKHands-On GPU Programming with Python and CUDA

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 Features Expand your background in GPU programming—PyCUDA, scikit-cuda, and Nsight Effectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver Apply GPU programming to modern data science applications Book Description Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how

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

The OpenCL Programming Book: parallel Programming for MultiCore CPU and GPU
  • Author : Anonim
  • Publisher : Fixstars
  • Release Date : 2023-02-01
  • ISBN : 0987654321XXX
GET THIS BOOKThe OpenCL Programming Book: parallel Programming for MultiCore CPU and GPU

Programming Massively Parallel Processors

Programming Massively Parallel Processors
  • Author : David B. Kirk,Wen-mei W. Hwu
  • Publisher : Newnes
  • Release Date : 2012-12-31
  • ISBN : 9780123914187
GET THIS BOOKProgramming Massively Parallel Processors

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

Parallel Programming

Parallel Programming
  • Author : Thomas Rauber,Gudula Rünger
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-06-13
  • ISBN : 9783642378010
GET THIS BOOKParallel Programming

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

Professional CUDA C Programming

Professional CUDA C Programming
  • Author : John Cheng,Max Grossman,Ty McKercher
  • Publisher : John Wiley & Sons
  • Release Date : 2014-09-09
  • ISBN : 9781118739327
GET THIS BOOKProfessional CUDA C Programming

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

Parallel and Concurrent Programming in Haskell

Parallel and Concurrent Programming in Haskell
  • Author : Simon Marlow
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2013-07-12
  • ISBN : 9781449335922
GET THIS BOOKParallel and Concurrent Programming in Haskell

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

CUDA Application Design and Development

CUDA Application Design and Development
  • Author : Rob Farber
  • Publisher : Elsevier
  • Release Date : 2011-10-31
  • ISBN : 9780123884268
GET THIS BOOKCUDA Application Design and Development

The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries."--Pub. desc.

CUDA Programming

CUDA Programming
  • Author : Shane Cook
  • Publisher : Newnes
  • Release Date : 2012-11-13
  • ISBN : 9780124159334
GET THIS BOOKCUDA Programming

'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.

CUDA by Example

CUDA by Example
  • Author : Jason Sanders,Edward Kandrot
  • Publisher : Addison-Wesley Professional
  • Release Date : 2010-07-19
  • ISBN : 9780132180139
GET THIS BOOKCUDA by Example

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

Multicore Computing

Multicore Computing
  • Author : Sanguthevar Rajasekaran,Lance Fiondella,Mohamed Ahmed,Reda A. Ammar
  • Publisher : CRC Press
  • Release Date : 2013-12-12
  • ISBN : 9781439854358
GET THIS BOOKMulticore Computing

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

Heterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL
  • Author : Benedict Gaster,Lee Howes,David R. Kaeli,Perhaad Mistry,Dana Schaa
  • Publisher : Newnes
  • Release Date : 2012-11-13
  • ISBN : 9780124058941
GET THIS BOOKHeterogeneous Computing with OpenCL

Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address