Cuda Programming
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Cuda Programming
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Author : Shane Cook
language : en
Publisher: Newnes
Release Date : 2012-11-13
Cuda Programming written by Shane Cook and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-13 with Computers categories.
'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.
Professional Cuda C Programming
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Author : John Cheng
language : en
Publisher: John Wiley & Sons
Release Date : 2014-09-09
Professional Cuda C Programming written by John Cheng and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-09 with Computers categories.
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.
Cuda Programming Fundamentals
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-11
Cuda Programming Fundamentals written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-11 with Computers categories.
"CUDA Programming Fundamentals" CUDA Programming Fundamentals is a comprehensive guide designed for engineers, researchers, and students seeking to master parallel computing with NVIDIA’s CUDA platform. Beginning with the foundational differences between CPU and GPU architectures, this book details the evolution of CUDA as a transformative technology in general-purpose GPU computing. Readers are equipped with practical instructions for setting up the CUDA development environment across major operating systems and are introduced to the full breadth of the CUDA ecosystem and compilation model, ensuring a robust understanding before diving into hands-on programming. The core chapters break down CUDA’s programming model, elucidating the principles behind threads, blocks, and grids, while offering thorough explanations of device functions, kernel launches, and synchronization techniques. The book delves deeply into CUDA’s intricate memory architecture, covering global, shared, constant, and unified memory, as well as efficient memory allocation for complex, multi-dimensional data. Best practices for performance tuning are highlighted, with guidance on profiling tools, optimizing memory access patterns, minimizing warp divergence, and maximizing throughput—crucial skills for building scalable, high-performance applications. Advancing beyond fundamental concepts, the text explores advanced patterns for algorithm design, asynchronous programming with streams and events, and the integration of CUDA with Python, OpenGL, and distributed systems. Real-world techniques for debugging, profiling, and error handling are covered alongside strategies for multi-GPU and hybrid computing environments. With in-depth discussions on numerical precision, security, and maintainability, CUDA Programming Fundamentals prepares readers to harness the power of modern GPU hardware while anticipating future trends and innovations in the field of accelerated computing.
Hands On Gpu Programming With Python And Cuda
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Author : Dr. Brian Tuomanen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-27
Hands On Gpu Programming With Python And Cuda written by Dr. Brian Tuomanen and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-27 with Computers categories.
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.
Multicore And Gpu Programming
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Author : Gerassimos Barlas
language : en
Publisher: Morgan Kaufmann
Release Date : 2022-02-09
Multicore And Gpu Programming written by Gerassimos Barlas and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-09 with Computers categories.
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
Gpu Programming In Matlab
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Author : Nikolaos Ploskas
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-08-25
Gpu Programming In Matlab written by Nikolaos Ploskas and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-25 with Computers categories.
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
Embedded Software Design And Programming Of Multiprocessor System On Chip
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Author : Katalin Popovici
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-03
Embedded Software Design And Programming Of Multiprocessor System On Chip written by Katalin Popovici and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-03 with Computers categories.
Current multimedia and telecom applications require complex, heterogeneous multiprocessor system on chip (MPSoC) architectures with specific communication infrastructure in order to achieve the required performance. Heterogeneous MPSoC includes different types of processing units (DSP, microcontroller, ASIP) and different communication schemes (fast links, non standard memory organization and access). Programming an MPSoC requires the generation of efficient software running on MPSoC from a high level environment, by using the characteristics of the architecture. This task is known to be tedious and error prone, because it requires a combination of high level programming environments with low level software design. This book gives an overview of concepts related to embedded software design for MPSoC. It details a full software design approach, allowing systematic, high-level mapping of software applications on heterogeneous MPSoC. This approach is based on gradual refinement of hardware/software interfaces and simulation models allowing to validate the software at different abstraction levels. This book combines Simulink for high level programming and SystemC for the low level software development. This approach is illustrated with multiple examples of application software and MPSoC architectures that can be used for deep understanding of software design for MPSoC.
Introduction To Parallel Programming
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Author : Subodh Kumar
language : en
Publisher: Cambridge University Press
Release Date : 2023-01-05
Introduction To Parallel Programming written by Subodh Kumar and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-05 with Computers categories.
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.
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
An Introduction To Parallel Programming
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Author : Peter Pacheco
language : en
Publisher: Morgan Kaufmann
Release Date : 2021-08-27
An Introduction To Parallel Programming written by Peter Pacheco and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-27 with Computers categories.
An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs while adding coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach students how to compile, run and modify example programs. - Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples - Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models - A robust package of online ancillaries for instructors and students includes lecture slides, solutions manual, downloadable source code, and an image bank New to this edition: - New chapters on GPU programming and heterogeneous programming - New examples and exercises related to parallel algorithms