Gpu Programming In Matlab

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GPU Programming in MATLAB

Nikolaos Ploskas,Nikolaos Samaras
GPU Programming in MATLAB Book PDF

Author : Nikolaos Ploskas,Nikolaos Samaras
Publisher : Morgan Kaufmann
Page : 318 pages
File Size : 42,9 Mb
Release : 2016-08-25
Category : Computers
ISBN : 9780128051337

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GPU Programming in MATLAB by Nikolaos Ploskas,Nikolaos Samaras Pdf

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

Jung W. Suh,Youngmin Kim
Accelerating MATLAB with GPU Computing Book PDF

Author : Jung W. Suh,Youngmin Kim
Publisher : Newnes
Page : 259 pages
File Size : 51,9 Mb
Release : 2013-11-18
Category : Computers
ISBN : 9780124079168

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Accelerating MATLAB with GPU Computing by Jung W. Suh,Youngmin Kim Pdf

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

Yair M. Altman
Accelerating MATLAB Performance Book PDF

Author : Yair M. Altman
Publisher : CRC Press
Page : 785 pages
File Size : 41,8 Mb
Release : 2014-12-11
Category : Computers
ISBN : 9781482211306

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Accelerating MATLAB Performance by Yair M. Altman Pdf

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.

Recent Progress in Parallel and Distributed Computing

Wen-Jyi Hwang
Recent Progress in Parallel and Distributed Computing Book PDF

Author : Wen-Jyi Hwang
Publisher : BoD – Books on Demand
Page : 126 pages
File Size : 51,6 Mb
Release : 2017-07-19
Category : Computers
ISBN : 9789535133155

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Recent Progress in Parallel and Distributed Computing by Wen-Jyi Hwang Pdf

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

Accelerating MATLAB Performance

Yair M. Altman
Accelerating MATLAB Performance Book PDF

Author : Yair M. Altman
Publisher : CRC Press
Page : 790 pages
File Size : 42,5 Mb
Release : 2014-12-11
Category : Computers
ISBN : 9781482211290

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Accelerating MATLAB Performance by Yair M. Altman Pdf

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.

Proceedings of 2013 Chinese Intelligent Automation Conference

Zengqi Sun,Zhidong Deng
Proceedings of 2013 Chinese Intelligent Automation Conference Book PDF

Author : Zengqi Sun,Zhidong Deng
Publisher : Springer Science & Business Media
Page : 866 pages
File Size : 44,6 Mb
Release : 2013-07-10
Category : Technology & Engineering
ISBN : 9783642384608

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Proceedings of 2013 Chinese Intelligent Automation Conference by Zengqi Sun,Zhidong Deng Pdf

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.

GPU Computing Gems Jade Edition

Anonim
GPU Computing Gems Jade Edition Book PDF

Author : Anonim
Publisher : Elsevier
Page : 560 pages
File Size : 50,7 Mb
Release : 2011-11-02
Category : Computers
ISBN : 9780123859648

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GPU Computing Gems Jade Edition by Anonim Pdf

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 improved programming environments for GPUs Even more hands-on, proven techniques demonstrating how general purpose GPU computing is changing scientific research Distills the best practices of the community of CUDA programmers; each chapter provides insights and ideas as well as 'hands on' skills applicable to a variety of fields

Geometric Modelling, Numerical Simulation, and Optimization:

Geir Hasle,Knut-Andreas Lie,Ewald Quak
Geometric Modelling Numerical Simulation and Optimization Book PDF

Author : Geir Hasle,Knut-Andreas Lie,Ewald Quak
Publisher : Springer Science & Business Media
Page : 559 pages
File Size : 41,6 Mb
Release : 2007-06-10
Category : Mathematics
ISBN : 9783540687832

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Geometric Modelling, Numerical Simulation, and Optimization: by Geir Hasle,Knut-Andreas Lie,Ewald Quak Pdf

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)

Cheng Few Lee,John C Lee
Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes Book PDF

Author : Cheng Few Lee,John C Lee
Publisher : World Scientific
Page : 5053 pages
File Size : 44,8 Mb
Release : 2020-07-30
Category : Business & Economics
ISBN : 9789811202407

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Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) by Cheng Few Lee,John C Lee Pdf

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

Sachin Bhalekar
Frontiers in Fractional Calculus Book PDF

Author : Sachin Bhalekar
Publisher : Bentham Science Publishers
Page : 381 pages
File Size : 42,5 Mb
Release : 2018-03-21
Category : Mathematics
ISBN : 9781681085999

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Frontiers in Fractional Calculus by Sachin Bhalekar Pdf

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.

GPU Computing Gems Jade Edition

Wen-mei Hwu
GPU Computing Gems Jade Edition Book PDF

Author : Wen-mei Hwu
Publisher : Elsevier
Page : 562 pages
File Size : 54,5 Mb
Release : 2011-09-28
Category : Computers
ISBN : 9780123859631

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GPU Computing Gems Jade Edition by Wen-mei Hwu Pdf

"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"--

Hands-On GPU Programming with CUDA

Jaegeun Han,Bharatkumar Sharma
Hands On GPU Programming with CUDA Book PDF

Author : Jaegeun Han,Bharatkumar Sharma
Publisher : Unknown
Page : 508 pages
File Size : 49,9 Mb
Release : 2019-09-27
Category : Computers
ISBN : 1788996240

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Hands-On GPU Programming with CUDA by Jaegeun Han,Bharatkumar Sharma Pdf

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 to work with programming languages such as C, C++, and Python. With CUDA, you can leverage a GPU's parallel computing power for a range of high-performance computing applications in the fields of science, healthcare, and deep learning. Learn CUDA Programming will help you learn GPU parallel programming and understand its modern applications. In this book, you'll discover CUDA programming approaches for modern GPU architectures. You'll not only be guided through GPU features, tools, and APIs, you'll also learn how to analyze performance with sample parallel programming algorithms. This book will help you optimize the performance of your apps by giving insights into CUDA programming platforms with various libraries, compiler directives (OpenACC), and other languages. As you progress, you'll learn how additional computing power can be generated using multiple GPUs in a box or in multiple boxes. Finally, you'll explore how CUDA accelerates deep learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). By the end of this CUDA book, you'll be equipped with the skills you need to integrate the power of GPU computing in your applications. What you will learn Understand general GPU operations and programming patterns in CUDA Uncover the difference between GPU programming and CPU programming Analyze GPU application performance and implement optimization strategies Explore GPU programming, profiling, and debugging tools Grasp parallel programming algorithms and how to implement them Scale GPU-accelerated applications with multi-GPU and multi-nodes Delve into GPU programming platforms with accelerated libraries, Python, and OpenACC Gain insights into deep learning accelerators in CNNs and RNNs using GPUs Who this book is for This beginner-level book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and build modern applications. Basic C and C++ programming experience is assumed. For deep learning enthusiasts, this book covers Python InterOps, DL libraries, and practical examples on performance estimation.

Computer Vision in Control Systems-4

Margarita N. Favorskaya,Lakhmi C. Jain
Computer Vision in Control Systems 4 Book PDF

Author : Margarita N. Favorskaya,Lakhmi C. Jain
Publisher : Springer
Page : 317 pages
File Size : 40,5 Mb
Release : 2017-10-25
Category : Technology & Engineering
ISBN : 9783319679945

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Computer Vision in Control Systems-4 by Margarita N. Favorskaya,Lakhmi C. Jain Pdf

The research book is a continuation of the authors’ previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The book gathers selected contributions addressing a number of real-life applications including the identification of handwritten texts, watermarking techniques, simultaneous localization and mapping for mobile robots, motion control systems for mobile robots, analysis of indoor human activity, facial image quality assessment, android device controlling, processing medical images, clinical decision-making and foot progression angle detection. Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, the book offers a timely guide for all PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

High-Performance Medical Image Processing

Sanjay Saxena,Sudip Paul
High Performance Medical Image Processing Book PDF

Author : Sanjay Saxena,Sudip Paul
Publisher : CRC Press
Page : 337 pages
File Size : 50,5 Mb
Release : 2022-07-07
Category : Computers
ISBN : 9781000410372

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High-Performance Medical Image Processing by Sanjay Saxena,Sudip Paul Pdf

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 computer engineering, biomedical engineering and electrical engineering based on artificial intelligence, parallel computing, high performance computing, and machine learning and its applications in medical imaging.

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision

L. Ashok Kumar,D. Karthika Renuka
Deep Learning Approach for Natural Language Processing Speech and Computer Vision Book PDF

Author : L. Ashok Kumar,D. Karthika Renuka
Publisher : CRC Press
Page : 251 pages
File Size : 41,8 Mb
Release : 2023-05-22
Category : Business & Economics
ISBN : 9781000875607

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Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision by L. Ashok Kumar,D. Karthika Renuka Pdf

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech, and computer vision tasks. It simplifies and presents the concepts of deep learning in a comprehensive manner, with suitable, full-fledged examples of deep learning models, with an aim to bridge the gap between the theoretical and the applications using case studies with code, experiments, and supporting analysis. Features: Covers latest developments in deep learning techniques as applied to audio analysis, computer vision, and natural language processing. Introduces contemporary applications of deep learning techniques as applied to audio, textual, and visual processing. Discovers deep learning frameworks and libraries for NLP, speech, and computer vision in Python. Gives insights into using the tools and libraries in Python for real-world applications. Provides easily accessible tutorials and real-world case studies with code to provide hands-on experience. This book is aimed at researchers and graduate students in computer engineering, image, speech, and text processing.