GPU 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 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

Produk Detail:

  • Author : Nikolaos Ploskas
  • Publisher : Morgan Kaufmann
  • Pages : 318 pages
  • ISBN : 0128051337
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKGPU Programming in MATLAB

GPU Programming in MATLAB

GPU Programming in MATLAB
  • Author : Nikolaos Ploskas,Nikolaos Samaras
  • Publisher : Morgan Kaufmann
  • Release : 25 August 2016
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

Accelerating MATLAB with GPU Computing

Accelerating MATLAB with GPU Computing
  • Author : Jung W. Suh,Youngmin Kim
  • Publisher : Newnes
  • Release : 18 November 2013
GET THIS BOOKAccelerating MATLAB with GPU Computing

Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the

Accelerating MATLAB Performance

Accelerating MATLAB Performance
  • Author : Yair M. Altman
  • Publisher : CRC Press
  • Release : 11 December 2014
GET THIS BOOKAccelerating MATLAB Performance

The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for "serious" applications. One of the main complaints is that MATLAB is just too slow. Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to greatly improve MATLAB program speed. Packed with thousands of helpful tips, it leaves no stone unturned, discussing every aspect of MATLAB. Ideal for novices and professionals alike, the book describes MATLAB performance in a scale

MATLAB

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  • Author : Kelly Bennett
  • Publisher : BoD – Books on Demand
  • Release : 08 September 2014
GET THIS BOOKMATLAB

MATLAB is an indispensable asset for scientists, researchers, and engineers. The richness of the MATLAB computational environment combined with an integrated development environment (IDE) and straightforward interface, toolkits, and simulation and modeling capabilities, creates a research and development tool that has no equal. From quick code prototyping to full blown deployable applications, MATLAB stands as a de facto development language and environment serving the technical needs of a wide range of users. As a collection of diverse applications, each book

Understanding LTE with MATLAB

Understanding LTE with MATLAB
  • Author : Houman Zarrinkoub
  • Publisher : John Wiley & Sons
  • Release : 28 January 2014
GET THIS BOOKUnderstanding LTE with MATLAB

An introduction to technical details related to the PhysicalLayer of the LTE standard with MATLAB® The LTE (Long Term Evolution) and LTE-Advanced are among thelatest mobile communications standards, designed to realize thedream of a truly global, fast, all-IP-based, secure broadbandmobile access technology. This book examines the Physical Layer (PHY) of the LTE standardsby incorporating three conceptual elements: an overview of thetheory behind key enabling technologies; a concise discussionregarding standard specifications; and the MATLAB® algorithmsneeded to simulate the standard. The use

Recent Progress in Parallel and Distributed Computing

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  • Author : Wen-Jyi Hwang
  • Publisher : BoD – Books on Demand
  • Release : 19 July 2017
GET THIS BOOKRecent Progress in Parallel and Distributed Computing

Parallel and distributed computing has been one of the most active areas of research in recent years. The techniques involved have found significant applications in areas as diverse as engineering, management, natural sciences, and social sciences. This book reports state-of-the-art topics and advances in this emerging field. Completely up-to-date, aspects it examines include the following: 1) Social networks; 2) Smart grids; 3) Graphic processing unit computation; 4) Distributed software development tools; 5) Analytic hierarchy process and the analytic network process

Professional CUDA C Programming

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

GPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 13 January 2011
GET THIS BOOKGPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance scientific research. The first volume in Morgan Kaufmann's Applications of GPU Computing Series, this book offers the latest insights and research in computer vision, electronic design automation, and emerging data-intensive applications. It also covers life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing. This book is intended to help those who

CUDA for Engineers

CUDA for Engineers
  • Author : Duane Storti,Mete Yurtoglu
  • Publisher : Addison-Wesley Professional
  • Release : 02 November 2015
GET THIS BOOKCUDA for Engineers

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you’ll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects

Financial Modelling

Financial Modelling
  • Author : Joerg Kienitz,Daniel Wetterau
  • Publisher : John Wiley & Sons
  • Release : 18 February 2013
GET THIS BOOKFinancial Modelling

Financial modelling Theory, Implementation and Practice with Matlab Source Jörg Kienitz and Daniel Wetterau Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic

CUDA Programming

CUDA Programming
  • Author : Shane Cook
  • Publisher : Newnes
  • Release : 01 March 2021
GET THIS BOOKCUDA Programming

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

Accelerating MATLAB with GPU Computing

Accelerating MATLAB with GPU Computing
  • Author : Jung W. Suh,Youngmin Kim
  • Publisher : Newnes
  • Release : 18 November 2013
GET THIS BOOKAccelerating MATLAB with GPU Computing

Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the

Programming Massively Parallel Processors

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  • Author : David B. Kirk,Wen-mei W. Hwu
  • Publisher : Morgan Kaufmann
  • Release : 24 November 2016
GET THIS BOOKProgramming Massively Parallel Processors

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries,

CUDA Fortran for Scientists and Engineers

CUDA Fortran for Scientists and Engineers
  • Author : Gregory Ruetsch,Massimiliano Fatica
  • Publisher : Elsevier
  • Release : 11 September 2013
GET THIS BOOKCUDA Fortran for Scientists and Engineers

CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and