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Parallel Processing Developments by World Occam and Transputer User Group. Technical Meeting Pdf
Technical articles on the 19th meeting of the World Occam and Transputer User Group (WoTUG). They cover a wide range of topics from hardware applications to software tools for of parallel processing support; not solely related to transputers. Part of the book focusses on the retargeting of the occam compiler to a range of other processors.
Advances in Edge Computing: Massive Parallel Processing and Applications by F. Xhafa,A.K. Sangaiah Pdf
The rapid advance of Internet of Things (IoT) technologies has resulted in the number of IoT-connected devices growing exponentially, with billions of connected devices worldwide. While this development brings with it great opportunities for many fields of science, engineering, business and everyday life, it also presents challenges such as an architectural bottleneck – with a very large number of IoT devices connected to a rather small number of servers in Cloud data centers – and the problem of data deluge. Edge computing aims to alleviate the computational burden of the IoT for the Cloud by pushing some of the computations and logics of processing from the Cloud to the Edge of the Internet. It is becoming commonplace to allocate tasks and applications such as data filtering, classification, semantic enrichment and data aggregation to this layer, but to prevent this new layer from itself becoming another bottleneck for the whole computing stack from IoT to the Cloud, the Edge computing layer needs to be capable of implementing massively parallel and distributed algorithms efficiently. This book, Advances in Edge Computing: Massive Parallel Processing and Applications, addresses these challenges in 11 chapters. Subjects covered include: Fog storage software architecture; IoT-based crowdsourcing; the industrial Internet of Things; privacy issues; smart home management in the Cloud and the Fog; and a cloud robotic solution to assist medical applications. Providing an overview of developments in the field, the book will be of interest to all those working with the Internet of Things and Edge computing.
Advances in Distributed and Parallel Processing: Applications in optimization, fluid dynamics, and VLSI by Harry W. Tyrer Pdf
The progress in distributed and parallel computing has been accompanied by the concurrent arrival of hardware architectures, software, and algorithms. This series reviews particular areas in this field based on fundamental issues and the state of the art. It provides in-depth contributions that should be valuable to all professionals involved in the design, development, research, production and use of parallel and distributed processing systems.
Parallel Computing: Technology Trends by I. Foster,G.R. Joubert,L. Kučera Pdf
The year 2019 marked four decades of cluster computing, a history that began in 1979 when the first cluster systems using Components Off The Shelf (COTS) became operational. This achievement resulted in a rapidly growing interest in affordable parallel computing for solving compute intensive and large scale problems. It also directly lead to the founding of the Parco conference series. Starting in 1983, the International Conference on Parallel Computing, ParCo, has long been a leading venue for discussions of important developments, applications, and future trends in cluster computing, parallel computing, and high-performance computing. ParCo2019, held in Prague, Czech Republic, from 10 – 13 September 2019, was no exception. Its papers, invited talks, and specialized mini-symposia addressed cutting-edge topics in computer architectures, programming methods for specialized devices such as field programmable gate arrays (FPGAs) and graphical processing units (GPUs), innovative applications of parallel computers, approaches to reproducibility in parallel computations, and other relevant areas. This book presents the proceedings of ParCo2019, with the goal of making the many fascinating topics discussed at the meeting accessible to a broader audience. The proceedings contains 57 contributions in total, all of which have been peer-reviewed after their presentation. These papers give a wide ranging overview of the current status of research, developments, and applications in parallel computing.
Advances in Parallel Computing Technologies and Applications by D.J. Hemanth,M. Elhosney,T.N. Nguyen Pdf
Recent developments in parallel computing mean that the use of machine learning techniques and intelligence to handle the huge volume of available data have brought the faster solutions offered by advanced technologies to various fields of application. This book presents the proceedings of the Virtual International Conference on Advances in Parallel Computing Technologies and Applications (ICAPTA 2021), hosted in Justice Basheer Ahmed Sayeed College for women (formerly "S.I.E.T Women's College"), Chennai, India, and held online as a virtual event on 15 and 16 April 2021. The aim of the conference was to provide a forum for sharing knowledge in various aspects of parallel computing in communications systems and networking, including cloud and virtualization solutions, management technologies, and vertical application areas. It also provided a platform for scientists, researchers, practitioners and academicians to present and discuss the most recent innovations and trends, as well as the concerns and practical challenges encountered in this field. Included here are 52 full length papers, selected from over 100 submissions based on the reviews and comments of subject experts. Topics covered include parallel computing in communication, machine learning intelligence for parallel computing and parallel computing for software services in theoretical and practical aspects. Providing an overview of the latest developments in the field, the book will be of interest to all those whose work involves the use of parallel computing technologies.
Programming Massively Parallel Processors by David B. Kirk,Wen-mei W. Hwu Pdf
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
Mining Very Large Databases with Parallel Processing by Alex A. Freitas,Simon H. Lavington Pdf
Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms. The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers. It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science. The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.
Massively Parallel Processing Applications and Development by L. Dekker,W. Smit,J.C. Zuidervaart Pdf
The contributions of a diverse selection of international hardware and software specialists are assimilated in this book's exploration of the development of massively parallel processing (MPP). The emphasis is placed on industrial applications and collaboration with users and suppliers from within the industrial community consolidates the scope of the publication. From a practical point of view, massively parallel data processing is a vital step to further innovation in all areas where large amounts of data must be processed in parallel or in a distributed manner, e.g. fluid dynamics, meteorology, seismics, molecular engineering, image processing, parallel data base processing. MPP technology can make the speed of computation higher and substantially reduce the computational costs. However, to achieve these features, the MPP software has to be developed further to create user-friendly programming systems and to become transparent for present-day computer software. Application of novel electro-optic components and devices is continuing and will be a key for much more general and powerful architectures. Vanishing of communication hardware limitations will result in the elimination of programming bottlenecks in parallel data processing. Standardization of the functional characteristics of a programming model of massively parallel computers will become established. Then efficient programming environments can be developed. The result will be a widespread use of massively parallel processing systems in many areas of application.
Parallel Computing is Everywhere by S. Bassini,M. Danelutto,P. Dazzi Pdf
The most powerful computers work by harnessing the combined computational power of millions of processors, and exploiting the full potential of such large-scale systems is something which becomes more difficult with each succeeding generation of parallel computers. Alternative architectures and computer paradigms are increasingly being investigated in an attempt to address these difficulties. Added to this, the pervasive presence of heterogeneous and parallel devices in consumer products such as mobile phones, tablets, personal computers and servers also demands efficient programming environments and applications aimed at small-scale parallel systems as opposed to large-scale supercomputers. This book presents a selection of papers presented at the conference: Parallel Computing (ParCo2017), held in Bologna, Italy, on 12 to 15 September 2017. The conference included contributions about alternative approaches to achieving High Performance Computing (HPC) to potentially surpass exa- and zetascale performances, as well as papers on the application of quantum computers and FPGA processors. These developments are aimed at making available systems better capable of solving intensive computational scientific/engineering problems such as climate models, security applications and classic NP-problems, some of which cannot currently be managed by even the most powerful supercomputers available. New areas of application, such as robotics, AI and learning systems, data science, the Internet of Things (IoT), and in-car systems and autonomous vehicles were also covered. As always, ParCo2017 attracted a large number of notable contributions covering present and future developments in parallel computing, and the book will be of interest to all those working in the field.
Parallel programming is designed for the use of parallel computer systems for solving time-consuming problems that cannot be solved on a sequential computer in a reasonable time. These problems can be divided into two classes: 1. Processing large data arrays (including processing images and signals in real time); 2. Simulation of complex physical processes and chemical reactions For each of these classes, prospective methods are designed for solving problems. For data processing, one of the most promising technologies is the use of artificial neural networks. Particles-in-cell method and cellular automata are very useful for simulation. Problems of scalability of parallel algorithms and the transfer of existing parallel programs to future parallel computers are very acute now. An important task is to optimise the use of the equipment (including the CPU cache) of parallel computers. Along with parallelising information processing, it is essential to ensure the processing reliability by the relevant organisation of systems of concurrent interacting processes. From the perspective of creating qualitative parallel programs, it is important to develop advanced methods of learning parallel programming. The above reasons are the basis for the creation of this book, chapters of which are devoted to solving these problems. We hope this book will be of interest to researchers, students and all those working in the field of parallel programming and high performance computing.
Parallel Scientific Computing and Optimization by Raimondas Ciegis,David Henty,Bo Kågström,Julius Žilinskas Pdf
Parallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including survey chapters and surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix computations, parallel optimization, management of parallel programming models and data, with the largest focus on parallel scientific computing in industrial applications. This volume is intended for scientists and graduate students specializing in computer science and applied mathematics who are engaged in parallel scientific computing.
Parallel Processing for Scientific Computing by Michael A. Heroux,Padma Raghavan,Horst D. Simon Pdf
Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.
ParCo2007 marks a quarter of a century of the international conferences on parallel computing that started in Berlin in 1983. The aim of the conference is to give an overview of the developments, applications and future trends in high-performance computing for various platforms.
