CUDA Programming

• Author : Shane Cook
• Publisher : Newnes
• Release : 28 December 2012

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction 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. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to

• Author : John Cheng,Max Grossman,Ty McKercher
• Publisher : John Wiley & Sons
• Release : 09 September 2014

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

• Author : Dr. Brian Tuomanen
• Publisher : Packt Publishing Ltd
• Release : 27 November 2018

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

• Author : Tolga Soyata
• Publisher : CRC Press
• Release : 19 January 2018

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism

• Author : Nikolaos Ploskas,Nikolaos Samaras
• Publisher : Morgan Kaufmann
• Release : 25 August 2016

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

• Author : Gerassimos Barlas
• Publisher : Morgan Kaufmann
• Release : 05 May 2022

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

• Author : Katalin Popovici,Frédéric Rousseau,Ahmed A. Jerraya,Marilyn Wolf
• Publisher : Springer Science & Business Media
• Release : 03 March 2010

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

• Author : Shane Cook
• Publisher : Newnes
• Release : 13 November 2012

'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.

• Author : Zoltan Horvath,Viktoria Zsok
• Publisher : Intellect Books
• Release : 10 October 2013

Volume 10 in the Trends in Functional Programming (TFP) series presents some of the latest research results in the implementation of functional programming languages and the practice of functional programming. It contains a peer-reviewed selection of the best articles presented at the 2009 Tenth Symposium on Trends in Functional Programming held in Komárno, Slovakia. TFP 2009 was co-located with the Third Central European Functional Programming School (CEFP 2009) and organized by the Department of Programming Languages and Compilers, Faculty of Informatics, Eötvö

• Author : Nicholas Wilt
• Publisher : Addison-Wesley
• Release : 11 June 2013

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

• Author : David B. Kirk,Wen-mei W. Hwu
• Publisher : Elsevier
• Release : 22 February 2010

Programming Massively Parallel Processors discusses the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This book describes computational thinking techniques that will enable students to think about problems in ways that are amenable to high-performance parallel computing. It utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for

• Author : Peter Pacheco,Matthew Malensek
• Publisher : Morgan Kaufmann
• Release : 27 August 2021

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

• Author : Thomas Rauber,Gudula Rünger
• Publisher : Springer Nature
• Release : 06 May 2023

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

• Author : José Nelson Amaral
• Publisher : Springer Science & Business Media
• Release : 01 December 2008

This book constitutes the thoroughly refereed post-conference proceedings of the 21th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2008, held in Edmonton, Canada, in July/August 2008. The 18 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 35 submissions. The papers address all aspects of languages, compiler techniques, run-time environments, and compiler-related performance evaluation for parallel and high-performance computing and comprise also presentations on program analysis that are precursors of high performance in parallel environments.

• Author : Zengqi Sun,Zhidong Deng
• Publisher : Springer Science & Business Media
• Release : 10 July 2013

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and