GPU Programming in MATLAB Book

GPU Programming in MATLAB


  • Author : Nikolaos Ploskas
  • Publisher : Morgan Kaufmann
  • Release Date : 2016-08-25
  • Genre: Computers
  • Pages : 318
  • ISBN 10 : 9780128051337

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GPU Programming in MATLAB Excerpt :

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

Accelerating MATLAB with GPU Computing Book

Accelerating MATLAB with GPU Computing


  • Author : Jung W. Suh
  • Publisher : Newnes
  • Release Date : 2013-11-18
  • Genre: Computers
  • Pages : 258
  • ISBN 10 : 9780124079168

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Accelerating MATLAB with GPU Computing Excerpt :

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

Accelerating MATLAB Performance Book

Accelerating MATLAB Performance


  • Author : Yair M. Altman
  • Publisher : CRC Press
  • Release Date : 2014-12-11
  • Genre: Computers
  • Pages : 785
  • ISBN 10 : 9781482211306

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Accelerating MATLAB Performance Excerpt :

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 and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup. The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes both the application of standard industry techniques in MATLAB, as well as methods that are specific to MATLAB such as using different data types or built-in functions. The book covers MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB’s memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance. Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily. Supported by an active website, and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times.

Accelerating MATLAB with GPU Computing Book

Accelerating MATLAB with GPU Computing


  • Author : Jung W. Suh
  • Publisher : Morgan Kaufmann
  • Release Date : 2013-11-26
  • Genre: Computers
  • Pages : 248
  • ISBN 10 : 0124080804

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Accelerating MATLAB with GPU Computing Excerpt :

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

Recent Progress in Parallel and Distributed Computing Book

Recent Progress in Parallel and Distributed Computing


  • Author : Wen-Jyi Hwang
  • Publisher : BoD – Books on Demand
  • Release Date : 2017-07-19
  • Genre: Computers
  • Pages : 126
  • ISBN 10 : 9789535133155

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Recent Progress in Parallel and Distributed Computing Excerpt :

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 Programming in Matlab Book

Gpu Programming in Matlab


  • Author : Nikolaos Ploskas
  • Publisher : Morgan Kaufmann Publishers
  • Release Date : 2016-08-22
  • Genre: Uncategoriezed
  • Pages : 318
  • ISBN 10 : 0128051329

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Gpu Programming in Matlab Excerpt :

"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 specialize knowledge of GPU programming. Following sections cover built-in GPU-enabled features of MATLAB, including options to leverage GPUs across multicore or different computer systems. Finally, advanced material, including CUDA code in MATLAB and optimizing existing GPU applications are presented. Throughout the book, examples and source code 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 toolboxesExplains 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 fieldsIncludes source code, sample datasets, and lecture slides

Proceedings of 2013 Chinese Intelligent Automation Conference Book

Proceedings of 2013 Chinese Intelligent Automation Conference


  • Author : Zengqi Sun
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-07-10
  • Genre: Technology & Engineering
  • Pages : 866
  • ISBN 10 : 9783642384608

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Proceedings of 2013 Chinese Intelligent Automation Conference Excerpt :

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 Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

Accelerating MATLAB Performance Book

Accelerating MATLAB Performance


  • Author : Yair M. Altman
  • Publisher : CRC Press
  • Release Date : 2014-12-11
  • Genre: Computers
  • Pages : 790
  • ISBN 10 : 9781482211290

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Accelerating MATLAB Performance Excerpt :

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 and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup. The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes both the application of standard industry techniques in MATLAB, as well as methods that are specific to MATLAB such as using different data types or built-in functions. The book covers MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB’s memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance. Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily. Supported by an active website, and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times.

GPU Computing Gems Jade Edition Book

GPU Computing Gems Jade Edition


  • Author : Anonim
  • Publisher : Elsevier
  • Release Date : 2011-11-02
  • Genre: Computers
  • Pages : 560
  • ISBN 10 : 9780123859648

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GPU Computing Gems Jade Edition Excerpt :

GPU Computing Gems, Jade Edition, offers hands-on, proven techniques for general purpose GPU programming based on the successful application experiences of leading researchers and developers. One of few resources available that distills the best practices of the community of CUDA programmers, this second edition contains 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, and green computing. It covers new tools and frameworks for productive GPU computing application development and provides immediate benefit to researchers developing improved programming environments for GPUs. Divided into five sections, this book explains how GPU execution is achieved with algorithm implementation techniques and approaches to data structure layout. More specifically, it considers three general requirements: high level of parallelism, coherent memory access by threads within warps, and coherent control flow within warps. Chapters explore topics such as accelerating database searches; how to leverage the Fermi GPU architecture to further accelerate prefix operations; and GPU implementation of hash tables. There are also discussions on the state of GPU computing in interactive physics and artificial intelligence; programming tools and techniques for GPU computing; and the edge and node parallelism approach for computing graph centrality metrics. In addition, the book proposes an alternative approach that balances computation regardless of node degree variance. Software engineers, programmers, hardware engineers, and advanced students will find this book extremely useful. This second volume of GPU Computing Gems offers 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, green computing, and more Covers new tools and frameworks for productive GPU computing application development and offers immediate benefit to researchers developing

Geometric Modelling  Numerical Simulation  and Optimization  Book

Geometric Modelling Numerical Simulation and Optimization


  • Author : Geir Hasle
  • Publisher : Springer Science & Business Media
  • Release Date : 2007-06-10
  • Genre: Mathematics
  • Pages : 558
  • ISBN 10 : 9783540687832

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Geometric Modelling Numerical Simulation and Optimization Excerpt :

This edited volume addresses the importance of mathematics for industry and society by presenting highlights from contract research at the Department of Applied Mathematics at SINTEF, the largest independent research organization in Scandinavia. Examples range from computer-aided geometric design, via general purpose computing on graphics cards, to reservoir simulation for enhanced oil recovery. Contributions are written in a tutorial style.

Handbook Of Financial Econometrics  Mathematics  Statistics  And Machine Learning  In 4 Volumes  Book

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


  • Author : Cheng-few Lee
  • Publisher : World Scientific
  • Release Date : 2020-07-30
  • Genre: Business & Economics
  • Pages : 5056
  • ISBN 10 : 9789811202407

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Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes Excerpt :

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 light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

Frontiers in Fractional Calculus Book

Frontiers in Fractional Calculus


  • Author : Sachin Bhalekar
  • Publisher : Bentham Science Publishers
  • Release Date : 2018-03-21
  • Genre: Mathematics
  • Pages : 381
  • ISBN 10 : 9781681085999

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Frontiers in Fractional Calculus Excerpt :

This book brings together eleven topics on different aspects of fractional calculus in a single volume. It provides readers the basic knowledge of fractional calculus and introduces advanced topics and applications. The information in the book is presented in four parts: 1. Fractional Diffusion Equations: (i) solutions of fractional diffusion equations using wavelet methods, (ii) the maximum principle for time fractional diffusion equations, (iii) nonlinear sub-diffusion equations. 2. Mathematical Analysis: (i) shifted Jacobi polynomials for solving and identifying coupled fractional delay differential equations, (ii) the monotone iteration principle in the theory of Hadamard fractional delay differential equations, (iii) dynamics of fractional order modified Bhalekar-Gejji System, (iv) Grunwald-Letnikov derivatives. 3. Computational Techniques: GPU computing of special mathematical functions used in fractional calculus. 4. Reviews: (i) the popular iterative method NIM, (ii) fractional derivative with non-singular kernels, (iii) some open problems in fractional order nonlinear system This is a useful reference for researchers and graduate level mathematics students seeking knowledge about of fractional calculus and applied mathematics.

Understanding LTE with MATLAB Book

Understanding LTE with MATLAB


  • Author : Houman Zarrinkoub
  • Publisher : John Wiley & Sons
  • Release Date : 2014-01-28
  • Genre: Technology & Engineering
  • Pages : 512
  • ISBN 10 : 9781118443453

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Understanding LTE with MATLAB Excerpt :

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 of MATLAB®, a widely used technical computinglanguage, is one of the distinguishing features of this book.Through a series of MATLAB® programs, the author explores eachof the enabling technologies, pedagogically synthesizes an LTE PHYsystem model, and evaluates system performance at each stage.Following this step-by-step process, readers will achieve deeperunderstanding of LTE concepts and specifications throughsimulations. Key Features: • Accessible, intuitive, and progressive; one of the fewbooks to focus primarily on the modeling, simulation, andimplementation of the LTE PHY standard • Includes case studies and testbenches in MATLAB®,which build knowledge gradually and incrementally until afunctional specification for the LTE PHY is attained • Accompanying Web site includes all MATLAB® programs,together with PowerPoint slides and other illustrative examples Dr Houman Zarrinkoub has served as a development manager andnow as a senior product manager with MathWorks, based inMassachusetts, USA. Within his 12 years at MathWorks, he has beenresponsible for multiple signal processing and communicationssoftware tools. Prior to MathWorks, he was a research scientist inthe Wireless Group at Nortel Networks, where he contributed tomultiple standardization projects for 3G mobile technologies. Hehas been awarded multiple patents on topics related to computersimulations. He hold

Digital Image Processing Book

Digital Image Processing


  • Author : Uvais Qidwai
  • Publisher : CRC Press
  • Release Date : 2009-10-15
  • Genre: Computers
  • Pages : 314
  • ISBN 10 : 9781420079517

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Digital Image Processing Excerpt :

Avoiding heavy mathematics and lengthy programming details, Digital Image Processing: An Algorithmic Approach with MATLAB® presents an easy methodology for learning the fundamentals of image processing. The book applies the algorithms using MATLAB®, without bogging down students with syntactical and debugging issues. One chapter can typically be completed per week, with each chapter divided into three sections. The first section presents theoretical topics in a very simple and basic style with generic language and mathematics. The second section explains the theoretical concepts using flowcharts to streamline the concepts and to form a foundation for students to code in any programming language. The final section supplies MATLAB codes for reproducing the figures presented in the chapter. Programming-based exercises at the end of each chapter facilitate the learning of underlying concepts through practice. This textbook equips undergraduate students in computer engineering and science with an essential understanding of digital image processing. It will also help them comprehend more advanced topics and sophisticated mathematical material in later courses. A color insert is included in the text while various instructor resources are available on the author’s website.

High Performance Medical Image Processing Book

High Performance Medical Image Processing


  • Author : Sanjay Saxena
  • Publisher : CRC Press
  • Release Date : 2022-07-07
  • Genre: Computers
  • Pages : 337
  • ISBN 10 : 9781000410372

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High Performance Medical Image Processing Excerpt :

The processing of medical images in a reasonable timeframe and with high definition is very challenging. This volume helps to meet that challenge by presenting a thorough overview of medical imaging modalities, its processing, high-performance computing, and the need to embed parallelism in medical image processing techniques to achieve efficient and fast results. With contributions from researchers from prestigious laboratories and educational institutions, High-Performance Medical Image Processing provides important information on medical image processing techniques, parallel computing techniques, and embedding parallelism in different image processing techniques. A comprehensive review of parallel algorithms in medical image processing problems is a key feature of this book. The volume presents the relevant theoretical frameworks and the latest empirical research findings in the area and provides detailed descriptions about the diverse high-performance techniques. Topics discussed include parallel computing, multicore architectures and their applications in image processing, machine learning applications, conventional and advanced magnetic resonance imaging methods, hyperspectral image processing, algorithms for segmenting 2D slices for 3D viewing, and more. Case studies, such as on the detection of cancer tumors, expound on the information presented. Key features: Provides descriptions of different medical imaging modalities and their applications Discusses the basics and advanced aspects of parallel computing with different multicore architectures Expounds on the need for embedding data and task parallelism in different medical image processing techniques Presents helpful examples and case studies of the discussed methods This book will be valuable for professionals, researchers, and students working in the field of healthcare engineering, medical imaging technology, applications in machine and deep learning, and more. It is also appropriate for courses in comp