Accelerating 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 basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB codes to better utilize the computational power of GPUs, and integrating them into commercial software products. Throughout the book, they demonstrate many example codes that can be used as templates of C-MEX and CUDA codes for readers’ projects. Download example codes from the publisher's website: http://booksite.elsevier.com/9780124080805/ Shows how to accelerate MATLAB codes through the GPU for parallel processing, with minimal hardware knowledge Explains the related background on hardware, architecture and programming for ease of use Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects

Produk Detail:

  • Author : Jung W. Suh
  • Publisher : Newnes
  • Pages : 258 pages
  • ISBN : 0124079164
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKAccelerating MATLAB with GPU Computing

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

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 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

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

Recent Progress in Parallel and Distributed Computing

Recent Progress in Parallel and Distributed Computing
  • 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

GPU Computing Gems

GPU Computing Gems
  • Author : Wen-mei W. Hwu
  • Publisher : Elsevier
  • Release : 06 December 2021
GET THIS BOOKGPU Computing Gems

"Since the introduction of CUDA in 2007, more than 100 million computers with CUDA capable GPUs have been shipped to end users. GPU computing application developers can now expect their application to have a mass market. With the introduction of OpenCL in 2010, researchers can now expect to develop GPU applications that can run on hardware from multiple vendors"--

Business Process Management Workshops

Business Process Management Workshops
  • Author : Manfred Reichert,Hajo A. Reijers
  • Publisher : Springer
  • Release : 25 July 2016
GET THIS BOOKBusiness Process Management Workshops

This book constitutes the refereed proceedings of ten international workshops held in Innsbruck, Austria, in conjunction with the 13th International Conference on Business Process Management, BPM 2015, in September 2015. The seven workshops comprised Adaptive Case Management and other Non-workflow Approaches to BPM (AdaptiveCM 2015), Business Process Intelligence (BPI 2015), Social and Human Aspects of Business Process Management (BPMS2 2015), Data- and Artifact-centric BPM (DAB 2015), Decision Mining and Modeling for Business Processes (DeMiMoP 2015), Process Engineering (IWPE 2015), and Theory and Applications of Process Visualization (TaProViz 2015). The 42

Self-Organizing Migrating Algorithm

Self-Organizing Migrating Algorithm
  • Author : Donald Davendra,Ivan Zelinka
  • Publisher : Springer
  • Release : 04 February 2016
GET THIS BOOKSelf-Organizing Migrating Algorithm

This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas.

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

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

Hands-On GPU Programming with CUDA

Hands-On GPU Programming with CUDA
  • Author : Jaegeun Han,Bharatkumar Sharma
  • Publisher : Unknown Publisher
  • Release : 27 September 2019
GET THIS BOOKHands-On GPU Programming with CUDA

Explore different GPU programming methods using libraries and directives, such as OpenACC, with extension to languages such as C, C++, and Python Key Features Learn parallel programming principles and practices and performance analysis in GPU computing Get to grips with distributed multi GPU programming and other approaches to GPU programming Understand how GPU acceleration in deep learning models can improve their performance Book Description Compute Unified Device Architecture (CUDA) is NVIDIA's GPU computing platform and application programming interface. It's designed

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)
  • Author : Cheng-few Lee,John C Lee
  • Publisher : World Scientific
  • Release : 30 July 2020
GET THIS BOOKHandbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in

Undocumented Secrets of MATLAB-Java Programming

Undocumented Secrets of MATLAB-Java Programming
  • Author : Yair M. Altman
  • Publisher : CRC Press
  • Release : 05 December 2011
GET THIS BOOKUndocumented Secrets of MATLAB-Java Programming

For a variety of reasons, the MATLAB®-Java interface was never fully documented. This is really quite unfortunate: Java is one of the most widely used programming languages, having many times the number of programmers and programming resources as MATLAB. Also unfortunate is the popular claim that while MATLAB is a fine programming platform for prototyping, it is not suitable for real-world, modern-looking applications. Undocumented Secrets of MATLAB®-Java Programming aims to correct this misconception. This book shows how using

Heterogeneous Computing Architectures

Heterogeneous Computing Architectures
  • Author : Olivier Terzo,Karim Djemame,Alberto Scionti,Clara Pezuela
  • Publisher : CRC Press
  • Release : 10 September 2019
GET THIS BOOKHeterogeneous Computing Architectures

Heterogeneous Computing Architectures: Challenges and Vision provides an updated vision of the state-of-the-art of heterogeneous computing systems, covering all the aspects related to their design: from the architecture and programming models to hardware/software integration and orchestration to real-time and security requirements. The transitions from multicore processors, GPU computing, and Cloud computing are not separate trends, but aspects of a single trend-mainstream; computers from desktop to smartphones are being permanently transformed into heterogeneous supercomputer clusters. The reader will get an