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Accelerating Matlab With Gpu Computing
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Book Synopsis Accelerating MATLAB with GPU Computing by : Jung W. Suh
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
Book Synopsis Accelerating MATLAB Performance by : Yair M. Altman
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
Book Synopsis Accelerating MATLAB Performance by : Yair M. Altman
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 790 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 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.
Book Synopsis GPU Programming in MATLAB by : Nikolaos Ploskas
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
Book Synopsis GPU Computing Gems Jade Edition by : Wen-mei Hwu
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"--
Book Synopsis The Elements of MATLAB Style by : Richard K. Johnson
Download or read book The Elements of MATLAB Style written by Richard K. Johnson and published by Cambridge University Press. This book was released on 2010-12-31 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Elements of MATLAB Style is a guide for both new and experienced MATLAB programmers. It provides a comprehensive collection of standards and guidelines for creating solid MATLAB code that will be easy to understand, enhance, and maintain. It is written for both individuals and those working in teams in which consistency is critical. This is the only book devoted to MATLAB style and best programming practices, focusing on how MATLAB code can be written in order to maximize its effectiveness. Just as Strunk and White's The Elements of Style provides rules for writing in the English language, this book provides conventions for formatting, naming, documentation, programming and testing. It includes many concise examples of correct and incorrect usage, as well as coverage of the latest language features. The author also provides recommendations on use of the integrated development environment features that help produce better, more consistent software.
Book Synopsis Spectral Methods in MATLAB by : Lloyd N. Trefethen
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.
Book Synopsis Undocumented Secrets of MATLAB-Java Programming by : Yair M. Altman
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
Book Synopsis Recent Progress in Parallel and Distributed Computing by : Wen-Jyi Hwang
Download or read book Recent Progress in Parallel and Distributed Computing written by Wen-Jyi Hwang and published by BoD – Books on Demand. This book was released on 2017-07-19 with total page 126 pages. Available in PDF, EPUB and Kindle. Book 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
Book Synopsis Numerical Computations with GPUs by : Volodymyr Kindratenko
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.
Book Synopsis Numerical Computing with MATLAB by : Cleve B. Moler
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.
Book Synopsis Self-Organizing Migrating Algorithm by : Donald Davendra
Download or read book Self-Organizing Migrating Algorithm written by Donald Davendra and published by Springer. This book was released on 2016-02-04 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.
Book Synopsis Professional CUDA C Programming by : John Cheng
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.
Book Synopsis Business Process Management Workshops by : Manfred Reichert
Download or read book Business Process Management Workshops written by Manfred Reichert and published by Springer. This book was released on 2016-07-25 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 revised papers presented were carefully reviewed and selected from 104 submissions. In addition, four short papers and one keynote (from TAProViz) are also included in this book.
Book Synopsis High performance computing for solving large sparse systems. Optical diffraction tomography as a case of study by : Gloria Ortega López
Download or read book High performance computing for solving large sparse systems. Optical diffraction tomography as a case of study written by Gloria Ortega López and published by Universidad Almería. This book was released on 2015-04-14 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis, entitled €High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study€ investigates the computational issues related to the resolution of linear systems of equations which come from the discretization of physical models described by means of Partial Differential Equations (PDEs). These physical models are conceived for the description of the space-temporary behavior of some physical phenomena f(x, y, z, t) in terms of their variations (partial derivative) with respect to the dependent variables of the phenomena. There is a wide variety of discretization methods for PDEs. Two of the most well-known methods are the Finite Difference Method (FDM) and the Finite Element Method (FEM). Both methods result in an algebraic description of the model that can be translated into the approach of a linear system of equations of type (Ax = b), where A is a sparse matrix (a high percentage of zero elements) whose size depends on the required accuracy of the modeled phenomena. This thesis begins with the algebraic description of the model associated with the physical phenomena, and the work herein has been focused on the design of techniques and computational models that allow the resolution of these linear systems of equations. The main interest of this study is specially focused on models which require a high level of discretization and usually generate sparse matrices, A, which have a highly sparse structure and large size. Literature characterizes these types of problems by their high demanding computational requirements (because of their fine degree of discretization) and the sparsity of the matrices involved, suggesting that these kinds of problems can only be solved using High Performance Computing techniques and architectures. One of the main goals of this thesis is the research of the possible alternatives which allow the implementation of routines to solve large and sparse linear systems of equations using High Performance Computing (HPC). The use of massively parallel platforms (GPUs) allows the acceleration of these routines, because they have several advantages for vectorial computation schemes. On the other hand, the use of distributed memory platforms allows the resolution of problems defined by matrices of enormous size. Finally, the combination of both techniques, distributed computation and multi-GPUs, will allow faster resolution of interesting problems in which large and sparse matrices are involved. In this line, one of the goals of this thesis is to supply the scientific community with implementations based on multi-GPU clusters to solve sparse linear systems of equations, which are the key in many scientific computations. The second part of this thesis is focused on a real physical problem of Optical Diffractional Tomography (ODT) based on holographic information. ODT is a non-damaging technique which allows the extraction of the shapes of objects with high accuracy. Therefore, this technique is very suitable to the in vivo study of real specimens, microorganisms, etc., and it also makes the investigation of their dynamics possible. A preliminary physical model based on a bidimensional reconstruction of the seeding particle distribution in fluids was proposed by J. Lobera and J.M. Coupland. However, its high computational cost (in both memory requirements and runtime) made compulsory the use of HPC techniques to extend the implementation to a three dimensional model. In the second part of this thesis, the implementation and validation of this physical model for the case of three dimensional reconstructions is carried out. In such implementation, the resolution of large and sparse linear systems of equations is required. Thus, some of the algebraic routines developed in the first part of the thesis have been used to implement computational strategies capable of solving the problem of 3D reconstruction based on ODT.
Book Synopsis Emerging Computing Techniques in Engineering by : Matthew N. O. Sadiku
Download or read book Emerging Computing Techniques in Engineering written by Matthew N. O. Sadiku and published by AuthorHouse. This book was released on 2022-11-17 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is divided into three volumes to cover all computing topics. This is the first volume and it has 23 chapters. It focuses on general computing techniques such as cloud computing, grid computing, pervasive computing, optical computing, web computing, parallel computing, distributed computing, high-performance computing, GPU computing, exascale & extreme computing, in-memory computing, embedded computing, quantum computing, and green computing
Book Synopsis CUDA for Engineers by : Duane Storti
Download or read book CUDA for Engineers written by Duane Storti and published by Addison-Wesley Professional. This book was released on 2015-11-02 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA’s parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA’s shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations
