Download or read book Parallel and Distributed Algorithms for High speed Image Processing written by Robert Louis Stevenson and published by . This book was released on 2000 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parallel and Distributed Methods for Image Processing written by and published by . This book was released on 1998 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parallel and Distributed Processing written by Jose Rolim and published by Springer Science & Business Media. This book was released on 2000-04-19 with total page 1332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings from the workshops held in conjunction with the IEEE International Parallel and Distributed Processing Symposium, IPDPS 2000, on 1-5 May 2000 in Cancun, Mexico. The workshopsprovidea forum for bringing together researchers,practiti- ers, and designers from various backgrounds to discuss the state of the art in parallelism.Theyfocusondi erentaspectsofparallelism,fromruntimesystems to formal methods, from optics to irregular problems, from biology to networks of personal computers, from embedded systems to programming environments; the following workshops are represented in this volume: { Workshop on Personal Computer Based Networks of Workstations { Workshop on Advances in Parallel and Distributed Computational Models { Workshop on Par. and Dist. Comp. in Image, Video, and Multimedia { Workshop on High-Level Parallel Prog. Models and Supportive Env. { Workshop on High Performance Data Mining { Workshop on Solving Irregularly Structured Problems in Parallel { Workshop on Java for Parallel and Distributed Computing { WorkshoponBiologicallyInspiredSolutionsto ParallelProcessingProblems { Workshop on Parallel and Distributed Real-Time Systems { Workshop on Embedded HPC Systems and Applications { Recon gurable Architectures Workshop { Workshop on Formal Methods for Parallel Programming { Workshop on Optics and Computer Science { Workshop on Run-Time Systems for Parallel Programming { Workshop on Fault-Tolerant Parallel and Distributed Systems All papers published in the workshops proceedings were selected by the p- gram committee on the basis of referee reports. Each paper was reviewed by independent referees who judged the papers for originality, quality, and cons- tency with the themes of the workshops.

Download or read book Parallel and High Performance Computing written by Robert Robey and published by Simon and Schuster. This book was released on 2021-08-24 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code

Download or read book Algorithms and Parallel Computing written by Fayez Gebali and published by John Wiley & Sons. This book was released on 2011-03-29 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.

Download or read book Algorithms for Image Processing and Computer Vision written by J. R. Parker and published by John Wiley & Sons. This book was released on 2010-11-29 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.

Download or read book High Performance Medical Image Processing written by Sanjay Saxena and published by CRC Press. This book was released on 2022-07-07 with total page 329 pages. Available in PDF, EPUB and Kindle. Book 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 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.

Download or read book Parallel Algorithms for Digital Image Processing Computer Vision and Neural Networks written by Ioannis Pitas and published by . This book was released on 1993-04-09 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: World-renowned contributors present papers concerning algorithms used on the latest generation of parallel machines (MIMD). Details key applications running the gamut from medical imaging, visualization and remote sensing to HDTV, demonstrating the large computational complexity necessary to perform these tasks.

Download or read book Topics in Parallel and Distributed Computing written by Sushil K Prasad and published by Morgan Kaufmann. This book was released on 2015-09-16 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topics in Parallel and Distributed Computing provides resources and guidance for those learning PDC as well as those teaching students new to the discipline. The pervasiveness of computing devices containing multicore CPUs and GPUs, including home and office PCs, laptops, and mobile devices, is making even common users dependent on parallel processing. Certainly, it is no longer sufficient for even basic programmers to acquire only the traditional sequential programming skills. The preceding trends point to the need for imparting a broad-based skill set in PDC technology. However, the rapid changes in computing hardware platforms and devices, languages, supporting programming environments, and research advances, poses a challenge both for newcomers and seasoned computer scientists. This edited collection has been developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts into courses throughout computer science curricula. Contributed and developed by the leading minds in parallel computing research and instruction Provides resources and guidance for those learning PDC as well as those teaching students new to the discipline Succinctly addresses a range of parallel and distributed computing topics Pedagogically designed to ensure understanding by experienced engineers and newcomers Developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts

Download or read book High Performance Adaptive Image Processing on Multi scale Hybrid Architectures written by and published by . This book was released on 2015 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In such an exciting age of information explosion, huge amount of visual data are produced continuously 24 hours, 7 days in both daily life and scientific research. Processing and storage of such a huge amount of data forms big challenges. Use of supercomputers tackles the need-for-speed challenge partially, but is blocked by its high cost of ownership and slow capacity growth. Distributed computing provides an attractive alternative which scale on demand, ranging from academic clusters to commercial clouds. In recent years, research on computer architecture also advanced significantly, resulting in wide deployment of multi-core and many core processors in both industries and daily life. To this end, this thesis explores how to apply the massively heterogeneous parallel distributed computing architectures for accelerating large-scale image processing applications effectively and efficiently. One step further, considering the actual gap between computing and imaging, the focus of this thesis invests efforts in exploring whether we can efficiently use high performance distributed computing systems to accelerate modern image processing algorithms. Combining the representative computing platforms with the selected image processing applications, four interesting aspects of fast image processing cases are studied in this thesis, namely: large-scale hyperspectral image analysis on multi-clusters platform, complex matrix manipulation on a cluster platform, matrix bidiagonalization on many-core platform, and fundamental matrix multiplication on a many-core accelerated cluster platform. Based on findings in each aspect, we conclude that parallel and distributed systems can give a lot of performance improvements to large-scale image processing applications, but are still hard to be deployed by image processing researchers. New research directions opened by this thesis include large-scale compute intensive application optimization with many-core clusters, complex time-consuming iterative matrix algorithms parallelization on grids, and identification of a generic hybrid multi-layer algorithmic parallelization methodology."--Samenvatting auteur.

Download or read book Algorithms and Tools for Parallel Computing on Heterogeneous Clusters written by Frédéric Desprez and published by Nova Publishers. This book was released on 2007 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features chapters which explore algorithms, programming languages, systems, tools and theoretical models aimed at high performance computing on heterogeneous networks of computers.

Download or read book Parallel and Distributed Computing Applications and Technologies written by K. M. Liew and published by Springer Science & Business Media. This book was released on 2004-12-02 with total page 914 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Parallel and Distributed Computing, Applications and Technologies; PDCAT 2004, held in Singapore in December 2004. The 173 papers presented were carefully reviewed and selected from 242 submissions. The papers focus on parallel and distributed computing from the perspectives of algorithms, networking and architecture, software systems and technologies, and applications. Besides classical topics from high performance computing, major recent developments are addressed, such as molecular computing, date mining, knowledge discovery, optical networks, secure computing and communications, wireless networks, mobile computing, component-based systems, Internet computing, and Web Technologies.

Download or read book High Performance Computing Systems and Applications written by Robert D. Kent and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: High Performance Computing Systems and Applications contains fully refereed papers from the 15th Annual Symposium on High Performance Computing. These papers cover both fundamental and applied topics in HPC: parallel algorithms, distributed systems and architectures, distributed memory and performance, high level applications, tools and solvers, numerical methods and simulation, advanced computing systems, and the emerging area of computational grids. High Performance Computing Systems and Applications is suitable as a secondary text for graduate level courses, and as a reference for researchers and practitioners in industry.

Download or read book Parallel Computation in Image Processing written by Steven L. Tanimoto and published by Cambridge International Series on Parallel Computation. This book was released on 2008-03 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advances in silicon and other computer technologies are making high speed, parallel image processing computers a reality. These processors will increasingly be massively parallel and embedded in cameras and other sensors. As these devices proliferate, designers of image processing systems need to understand the basic algorithms and programming techniques for realizing solutions to problems in image analysis, vision, data compression, and information retrieval. This book covers key parallel architectures and algorithms for processing images, including both the theory of massively parallel mesh-based architectures and the practical aspects of programming these systems. The techniques presented have applications to computer vision, image compression, image analysis, and information retrieval. The book can be used as a course text for students in electrical engineering and computer science at the graduate and advanced undergraduate levels and as a reference for researchers and working professionals.

Download or read book High Performance Deformable Image Registration Algorithms for Manycore Processors written by James Shackleford and published by Newnes. This book was released on 2013-06-28 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans. Demonstrates how to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithms Shows how to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs Provides Programming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU

Download or read book Parallel Architectures and Parallel Algorithms for Integrated Vision Systems written by Alok N. Choudary and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is one of the most complex and computationally intensive problem. Like any other computationally intensive problems, parallel pro cessing has been suggested as an approach to solving the problems in com puter vision. Computer vision employs algorithms from a wide range of areas such as image and signal processing, advanced mathematics, graph theory, databases and artificial intelligence. Hence, not only are the comput ing requirements for solving vision problems tremendous but they also demand computers that are efficient to solve problems exhibiting vastly dif ferent characteristics. With recent advances in VLSI design technology, Single Instruction Multiple Data (SIMD) massively parallel computers have been proposed and built. However, such architectures have been shown to be useful for solving a very limited subset of the problems in vision. Specifically, algorithms from low level vision that involve computations closely mimicking the architec ture and require simple control and computations are suitable for massively parallel SIMD computers. An Integrated Vision System (IVS) involves com putations from low to high level vision to be executed in a systematic fashion and repeatedly. The interaction between computations and information dependent nature of the computations suggests that architectural require ments for computer vision systems can not be satisfied by massively parallel SIMD computers.

Download or read book Multimodal Analytics for Next Generation Big Data Technologies and Applications written by Kah Phooi Seng and published by Springer. This book was released on 2019-07-18 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.