gpu programming in matlab

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Gpu Programming In Matlab

Author : Nikolaos Ploskas
ISBN : 9780128051337
Genre : Computers
File Size : 64. 77 MB
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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

Author : Jung W. Suh
ISBN : 9780124079168
Genre : Computers
File Size : 42. 46 MB
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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

Author : Wen-Jyi Hwang
ISBN : 9789535133155
Genre : Computers
File Size : 77. 58 MB
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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

Author : Yair M. Altman
ISBN : 9781482211306
Genre : Computers
File Size : 38. 23 MB
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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

Author :
ISBN : 9780123859648
Genre : Computers
File Size : 74. 87 MB
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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

Proceedings Of The Second International Conference On Soft Computing For Problem Solving Socpros 2012 December 28 30 2012

Author : B. V. Babu
ISBN : 9788132216025
Genre : Computers
File Size : 85. 73 MB
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The present book is based on the research papers presented in the International Conference on Soft Computing for Problem Solving (SocProS 2012), held at JK Lakshmipat University, Jaipur, India. This book provides the latest developments in the area of soft computing and covers a variety of topics, including mathematical modeling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, data mining, etc. The objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems that are otherwise difficult to solve by the usual and traditional methods. The book is directed to the researchers and scientists engaged in various fields of Science and Technology.

Archives Of Pathology Laboratory Medicine

Author :
ISBN : NWU:35558005694944
Genre : Diagnosis, Laboratory
File Size : 23. 35 MB
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Quantum Transport Modeling With Gpus

Author : Mohammed Harb
ISBN : OCLC:921888867
Genre :
File Size : 32. 69 MB
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"In this thesis, we have developed a parallel GPU accelerated code for carrying out transport calculations within the Non-Equilibrium Green's Function (NEGF) framework using the Tight-Binding (TB) model. We also discuss the theoretical, modelling, and computational issues that arise in this implementation. We demonstrate that a heterogenous implementation with CPUs and GPUs is superior to single processor, multiple processor, and massively parallel CPU-only implementations. The GPU-Matlab Interface (GMI) developed in this work for use in our NEGF-TB code is not application specific and can be used by researchers in any field without previous knowledge of GPU programming or multi-threaded programming. We also demonstrate that GMI competes very well with commercial packages.Finally, we apply our heterogenous NEGF-TB code to the study of electronic transport properties of Si nanowires and nanobeams. We investigate the effect of several kinds of structural defects on the conductance of such devices and demonstrate that our method can handle systems of over 200,000 atoms in a reasonable time scale while using just 1-4 GPUs." --

Engineering Applications Of Neural Networks

Author : Valeri Mladenov
ISBN : 9783319110714
Genre : Computers
File Size : 78. 74 MB
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This volume constitutes the refereed proceedings of the 15th International Conference on Engineering Applications of Neural Networks, EANN 2014, held in Sofia, Bulgaria, in September 2014. The 18 revised full papers presented together with 5 short papers were carefully reviewed and selected from 37 submissions. The papers demonstrate a variety of applications of neural networks and other computational intelligence approaches to challenging problems relevant to society and the economy. These include areas such as: environmental engineering, facial expression recognition, classification with parallelization algorithms, control of autonomous unmanned aerial vehicles, intelligent transport, flood forecasting, classification of medical images, renewable energy systems, intrusion detection, fault classification and general engineering.

Languages And Compilers For Parallel Computing

Author : Chen Ding
ISBN : 9783319527093
Genre : Computers
File Size : 55. 43 MB
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This book constitutes the thoroughly refereed post-conference proceedings of the 29th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2016, held in Rochester, NY, USA, in September 2016. The 20 revised full papers presented together with 4 short papers were carefully reviewed. The papers are organized in topical sections on large scale parallelism, resilience and persistence, compiler analysis and optimization, dynamic computation and languages, GPUs and private memory, and runt-time and performance analysis.

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