Download or read book GPU Programming in MATLAB written by Nikolaos Ploskas and published by Morgan Kaufmann. This book was released on 2016-08-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book 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

Download or read book Accelerating MATLAB with GPU Computing written by Jung W. Suh and published by Newnes. This book was released on 2013-11-18 with total page 259 pages. Available in PDF, EPUB and Kindle. Book 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

Download or read book Accelerating MATLAB Performance written by Yair M. Altman and published by CRC Press. This book was released on 2014-12-11 with total page 768 pages. Available in PDF, EPUB and Kindle. Book 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 tho

Download or read book GPU Computing Gems Jade Edition written by Wen-mei Hwu and published by Elsevier. This book was released on 2011-09-28 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--

Download or read book Undocumented Secrets of MATLAB Java Programming written by Yair M. Altman and published by CRC Press. This book was released on 2011-12-05 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Java can significantly improve MATLAB program appearance and functionality, and that this can be done easily and even without any prior Java knowledge. Readers are led step-by-step from simple to complex customizations. Code snippets, screenshots, and numerous online references are provided to enable the utilization of this book as both a sequential tutorial and as a random-access reference suited for immediate use. Java-savvy readers will find it easy to tailor code samples for their particular needs; for Java newcomers, an introduction to Java and numerous online references are provided. This book demonstrates how The MATLAB programming environment relies on Java for numerous tasks, including networking, data-processing algorithms and graphical user-interface (GUI) We can use MATLAB for easy access to external Java functionality, either third-party or user-created Using Java, we can extensively customize the MATLAB environment and application GUI, enabling the creation of visually appealing and usable applications

Download or read book Spectral Methods in MATLAB written by Lloyd N. Trefethen and published by SIAM. This book was released on 2000-07-01 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- Numerical Analysis.

Download or read book Professional CUDA C Programming written by John Cheng and published by John Wiley & Sons. This book was released on 2014-09-09 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 to explore both the "hard" and "soft" aspects of GPU programming. Computing architectures are experiencing a fundamental shift toward scalable parallel computing motivated by application requirements in industry and science. This book demonstrates the challenges of efficiently utilizing compute resources at peak performance, presents modern techniques for tackling these challenges, while increasing accessibility for professionals who are not necessarily parallel programming experts. The CUDA programming model and tools empower developers to write high-performance applications on a scalable, parallel computing platform: the GPU. However, CUDA itself can be difficult to learn without extensive programming experience. Recognized CUDA authorities John Cheng, Max Grossman, and Ty McKercher guide readers through essential GPU programming skills and best practices in Professional CUDA C Programming, including: CUDA Programming Model GPU Execution Model GPU Memory model Streams, Event and Concurrency Multi-GPU Programming CUDA Domain-Specific Libraries Profiling and Performance Tuning The book makes complex CUDA concepts easy to understand for anyone with knowledge of basic software development with exercises designed to be both readable and high-performance. For the professional seeking entrance to parallel computing and the high-performance computing community, Professional CUDA C Programming is an invaluable resource, with the most current information available on the market.

Download or read book Financial Modelling written by Joerg Kienitz and published by John Wiley & Sons. This book was released on 2013-02-18 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 and simulation techniques, and calibration even for exotic options. The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated. The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Lévy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk. The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model. Source code used for producing the results and analysing the models is provided on the author's dedicated website, http://www.mathworks.de/matlabcentral/fileexchange/authors/246981.

Download or read book Hands On GPU Programming with CUDA written by Jaegeun Han and published by . This book was released on 2019-09-27 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Numerical Computations with GPUs written by Volodymyr Kindratenko and published by Springer. This book was released on 2014-07-03 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together research on numerical methods adapted for Graphics Processing Units (GPUs). It explains recent efforts to adapt classic numerical methods, including solution of linear equations and FFT, for massively parallel GPU architectures. This volume consolidates recent research and adaptations, covering widely used methods that are at the core of many scientific and engineering computations. Each chapter is written by authors working on a specific group of methods; these leading experts provide mathematical background, parallel algorithms and implementation details leading to reusable, adaptable and scalable code fragments. This book also serves as a GPU implementation manual for many numerical algorithms, sharing tips on GPUs that can increase application efficiency. The valuable insights into parallelization strategies for GPUs are supplemented by ready-to-use code fragments. Numerical Computations with GPUs targets professionals and researchers working in high performance computing and GPU programming. Advanced-level students focused on computer science and mathematics will also find this book useful as secondary text book or reference.

Download or read book Understanding LTE with MATLAB written by Houman Zarrinkoub and published by John Wiley & Sons. This book was released on 2014-01-28 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to technical details related to the Physical Layer of the LTE standard with MATLAB® The LTE (Long Term Evolution) and LTE-Advanced are among the latest mobile communications standards, designed to realize the dream of a truly global, fast, all-IP-based, secure broadband mobile access technology. This book examines the Physical Layer (PHY) of the LTE standards by incorporating three conceptual elements: an overview of the theory behind key enabling technologies; a concise discussion regarding standard specifications; and the MATLAB® algorithms needed to simulate the standard. The use of MATLAB®, a widely used technical computing language, is one of the distinguishing features of this book. Through a series of MATLAB® programs, the author explores each of the enabling technologies, pedagogically synthesizes an LTE PHY system model, and evaluates system performance at each stage. Following this step-by-step process, readers will achieve deeper understanding of LTE concepts and specifications through simulations. Key Features: • Accessible, intuitive, and progressive; one of the few books to focus primarily on the modeling, simulation, and implementation of the LTE PHY standard • Includes case studies and testbenches in MATLAB®, which build knowledge gradually and incrementally until a functional 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 and now as a senior product manager with MathWorks, based in Massachusetts, USA. Within his 12 years at MathWorks, he has been responsible for multiple signal processing and communications software tools. Prior to MathWorks, he was a research scientist in the Wireless Group at Nortel Networks, where he contributed to multiple standardization projects for 3G mobile technologies. He has been awarded multiple patents on topics related to computer simulations. He holds a BSc degree in Electrical Engineering from McGill University and MSc and PhD degrees in Telecommunications from the Institut Nationale de la Recherche Scientifique, in Canada. www.wiley.com/go/zarrinkoub

Download or read book Numerical Computing with MATLAB written by Cleve B. Moler and published by SIAM. This book was released on 2010-08-12 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revised textbook for introductory courses in numerical methods, MATLAB and technical computing, which emphasises the use of mathematical software.

Download or read book Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and published by World Scientific. This book was released on 2020-07-30 with total page 5053 pages. Available in PDF, EPUB and Kindle. Book 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.

Download or read book MATLAB written by Kelly Bennett and published by BoD – Books on Demand. This book was released on 2014-09-08 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 chapter presents a novel application and use of MATLAB for a specific result.

Download or read book GPU Gems 2 written by Matt Pharr and published by Addison-Wesley Professional. This book was released on 2005 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: More useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.

Download or read book CUDA Application Design and Development written by Rob Farber and published by Elsevier. This book was released on 2011-10-31 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries."--Pub. desc.

Download or read book Highly Parallel Computing written by George S. Almasi and published by Addison Wesley Longman. This book was released on 1994 with total page 726 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition includes new exercises for each chapter, a quantitative treatment of speedup, seismic migration, using a workstation network as a parallel computer, recent changes in technology, more languages, fat trees, wormhole switching, new SIMD hardware, an expanded section on CM-2, new MIMD hardware, using workstation clusters as a MIMD system, and directory based caches. Annotation copyright by Book News, Inc., Portland, OR