High Performance Computing And Big Data Analysis

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High-Performance Big Data Computing

Author : Dhabaleswar K. Panda
Publisher : MIT Press
ISBN 13 : 0262369427
Total Pages : 275 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis High-Performance Big Data Computing by : Dhabaleswar K. Panda

Download or read book High-Performance Big Data Computing written by Dhabaleswar K. Panda and published by MIT Press. This book was released on 2022-08-02 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.

High-Performance Big-Data Analytics

Author : Pethuru Raj
Publisher : Springer
ISBN 13 : 331920744X
Total Pages : 443 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis High-Performance Big-Data Analytics by : Pethuru Raj

Download or read book High-Performance Big-Data Analytics written by Pethuru Raj and published by Springer. This book was released on 2015-10-16 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.

High Performance Computing for Big Data

Author : Chao Wang
Publisher : CRC Press
ISBN 13 : 1351651579
Total Pages : 360 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis High Performance Computing for Big Data by : Chao Wang

Download or read book High Performance Computing for Big Data written by Chao Wang and published by CRC Press. This book was released on 2017-10-16 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering. Features Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles Describes advanced algorithms for different big data application domains Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications. About the Editor Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.

Big Data and High Performance Computing

Author : L. Grandinetti
Publisher : IOS Press
ISBN 13 : 1614995834
Total Pages : 168 pages
Book Rating : 4.6/5 (149 download)

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Book Synopsis Big Data and High Performance Computing by : L. Grandinetti

Download or read book Big Data and High Performance Computing written by L. Grandinetti and published by IOS Press. This book was released on 2015-10-20 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data has been much in the news in recent years, and the advantages conferred by the collection and analysis of large datasets in fields such as marketing, medicine and finance have led to claims that almost any real world problem could be solved if sufficient data were available. This is of course a very simplistic view, and the usefulness of collecting, processing and storing large datasets must always be seen in terms of the communication, processing and storage capabilities of the computing platforms available. This book presents papers from the International Research Workshop, Advanced High Performance Computing Systems, held in Cetraro, Italy, in July 2014. The papers selected for publication here discuss fundamental aspects of the definition of Big Data, as well as considerations from practice where complex datasets are collected, processed and stored. The concepts, problems, methodologies and solutions presented are of much more general applicability than may be suggested by the particular application areas considered. As a result the book will be of interest to all those whose work involves the processing of very large data sets, exascale computing and the emerging fields of data science

High Performance Computing for Big Data

Author : Chao Wang
Publisher : CRC Press
ISBN 13 : 1498784003
Total Pages : 287 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis High Performance Computing for Big Data by : Chao Wang

Download or read book High Performance Computing for Big Data written by Chao Wang and published by CRC Press. This book was released on 2017-10-16 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering. Features Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles Describes advanced algorithms for different big data application domains Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications. About the Editor Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.

Conquering Big Data with High Performance Computing

Author : Ritu Arora
Publisher : Springer
ISBN 13 : 3319337424
Total Pages : 328 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Conquering Big Data with High Performance Computing by : Ritu Arora

Download or read book Conquering Big Data with High Performance Computing written by Ritu Arora and published by Springer. This book was released on 2016-09-16 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the resources and research projects that are bringing Big Data and High Performance Computing (HPC) on converging tracks. It demystifies Big Data and HPC for the reader by covering the primary resources, middleware, applications, and tools that enable the usage of HPC platforms for Big Data management and processing.Through interesting use-cases from traditional and non-traditional HPC domains, the book highlights the most critical challenges related to Big Data processing and management, and shows ways to mitigate them using HPC resources. Unlike most books on Big Data, it covers a variety of alternatives to Hadoop, and explains the differences between HPC platforms and Hadoop.Written by professionals and researchers in a range of departments and fields, this book is designed for anyone studying Big Data and its future directions. Those studying HPC will also find the content valuable.

New Frontiers in High Performance Computing and Big Data

Author : G. Fox
Publisher : IOS Press
ISBN 13 : 1614998167
Total Pages : 272 pages
Book Rating : 4.6/5 (149 download)

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Book Synopsis New Frontiers in High Performance Computing and Big Data by : G. Fox

Download or read book New Frontiers in High Performance Computing and Big Data written by G. Fox and published by IOS Press. This book was released on 2017-11-14 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the last four decades, parallel computing platforms have increasingly formed the basis for the development of high performance systems primarily aimed at the solution of intensive computing problems, and the application of parallel computing systems has also become a major factor in furthering scientific research. But such systems also offer the possibility of solving the problems encountered in the processing of large-scale scientific data sets, as well as in the analysis of Big Data in the fields of medicine, social media, marketing, economics etc. This book presents papers from the International Research Workshop on Advanced High Performance Computing Systems, held in Cetraro, Italy, in July 2016. The workshop covered a wide range of topics and new developments related to the solution of intensive and large-scale computing problems, and the contributions included in this volume cover aspects of the evolution of parallel platforms and highlight some of the problems encountered with the development of ever more powerful computing systems. The importance of future large-scale data science applications is also discussed. The book will be of particular interest to all those involved in the development or application of parallel computing systems.

High-Performance Modelling and Simulation for Big Data Applications

Author : Joanna Kołodziej
Publisher : Springer
ISBN 13 : 3030162729
Total Pages : 364 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis High-Performance Modelling and Simulation for Big Data Applications by : Joanna Kołodziej

Download or read book High-Performance Modelling and Simulation for Big Data Applications written by Joanna Kołodziej and published by Springer. This book was released on 2019-03-25 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.

Supercomputing Frontiers

Author : Rio Yokota
Publisher : Springer
ISBN 13 : 3319699539
Total Pages : 301 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Supercomputing Frontiers by : Rio Yokota

Download or read book Supercomputing Frontiers written by Rio Yokota and published by Springer. This book was released on 2018-03-20 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: It constitutes the refereed proceedings of the 4th Asian Supercomputing Conference, SCFA 2018, held in Singapore in March 2018. Supercomputing Frontiers will be rebranded as Supercomputing Frontiers Asia (SCFA), which serves as the technical programme for SCA18. The technical programme for SCA18 consists of four tracks: Application, Algorithms & Libraries Programming System Software Architecture, Network/Communications & Management Data, Storage & Visualisation The 20 papers presented in this volume were carefully reviewed nd selected from 60 submissions.

High-Performance Computing and Big Data Analysis

Author : Lucio Grandinetti
Publisher : Springer Nature
ISBN 13 : 3030334953
Total Pages : 514 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis High-Performance Computing and Big Data Analysis by : Lucio Grandinetti

Download or read book High-Performance Computing and Big Data Analysis written by Lucio Grandinetti and published by Springer Nature. This book was released on 2019-10-19 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised and selected papers from the Second International Congress on High-Performance Computing and Big Data Analysis, TopHPC 2019, held in Tehran, Iran, in April 2019. The 37 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 103 submissions. The papers in the volume are organized acording to the following topical headings: deep learning; big data analytics; Internet of Things.- data mining, neural network and genetic algorithms; performance issuesand quantum computing.

Big Data Technologies and Applications

Author : Borko Furht
Publisher : Springer
ISBN 13 : 3319445502
Total Pages : 405 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Big Data Technologies and Applications by : Borko Furht

Download or read book Big Data Technologies and Applications written by Borko Furht and published by Springer. This book was released on 2016-09-16 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.

Big Data and HPC: Ecosystem and Convergence

Author : L. Grandinetti
Publisher : IOS Press
ISBN 13 : 1614998825
Total Pages : 338 pages
Book Rating : 4.6/5 (149 download)

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Book Synopsis Big Data and HPC: Ecosystem and Convergence by : L. Grandinetti

Download or read book Big Data and HPC: Ecosystem and Convergence written by L. Grandinetti and published by IOS Press. This book was released on 2018-08-22 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the increasing need to solve complex problems, high-performance computing (HPC) is now one of the most fundamental infrastructures for scientific development in all disciplines, and it has progressed massively in recent years as a result. HPC facilitates the processing of big data, but the tremendous research challenges faced in recent years include: the scalability of computing performance for high velocity, high variety and high volume big data; deep learning with massive-scale datasets; big data programming paradigms on multi-core; GPU and hybrid distributed environments; and unstructured data processing with high-performance computing. This book presents 19 selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale era, held in Tehran, Iran, in April 2017. The book is divided into 3 sections: State of the Art and Future Scenarios, Big Data Challenges, and HPC Challenges, and will be of interest to all those whose work involves the processing of Big Data and the use of HPC.

Deep Learning and Edge Computing Solutions for High Performance Computing

Author : A. Suresh
Publisher : Springer Nature
ISBN 13 : 3030602656
Total Pages : 286 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Deep Learning and Edge Computing Solutions for High Performance Computing by : A. Suresh

Download or read book Deep Learning and Edge Computing Solutions for High Performance Computing written by A. Suresh and published by Springer Nature. This book was released on 2021-01-27 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.

Advances in High Performance Computing

Author : Ivan Dimov
Publisher : Springer Nature
ISBN 13 : 3030553477
Total Pages : 464 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Advances in High Performance Computing by : Ivan Dimov

Download or read book Advances in High Performance Computing written by Ivan Dimov and published by Springer Nature. This book was released on 2020-08-07 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every day we need to solve large problems for which supercomputers are needed. High performance computing (HPC) is a paradigm that allows to efficiently implement large-scale computational tasks on powerful supercomputers unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many challenging real world problems arising in engineering, economics, medicine and other areas can be formulated as large-scale computational tasks. The volume is a comprehensive collection of extended contributions from the High performance computing conference held in Borovets, Bulgaria, September 2019. This book presents recent advances in high performance computing. The topics of interest included into this volume are: HP software tools, Parallel Algorithms and Scalability, HPC in Big Data analytics, Modelling, Simulation & Optimization in a Data Rich Environment, Advanced numerical methods for HPC, Hybrid parallel or distributed algorithms. The volume is focused on important large-scale applications like Environmental and Climate Modeling, Computational Chemistry and Heuristic Algorithms.

Resource Management for Big Data Platforms

Author : Florin Pop
Publisher : Springer
ISBN 13 : 3319448811
Total Pages : 509 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Resource Management for Big Data Platforms by : Florin Pop

Download or read book Resource Management for Big Data Platforms written by Florin Pop and published by Springer. This book was released on 2016-10-27 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and their potential solutions.

High-Performance Big Data Computing

Author : Dhabaleswar K. Panda
Publisher : MIT Press
ISBN 13 : 0262369427
Total Pages : 275 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis High-Performance Big Data Computing by : Dhabaleswar K. Panda

Big Data Analytics for Sensor-Network Collected Intelligence

Author : Hui-Huang Hsu
Publisher : Morgan Kaufmann
ISBN 13 : 012809625X
Total Pages : 328 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Big Data Analytics for Sensor-Network Collected Intelligence by : Hui-Huang Hsu

Download or read book Big Data Analytics for Sensor-Network Collected Intelligence written by Hui-Huang Hsu and published by Morgan Kaufmann. This book was released on 2017-02-02 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people’s behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS Contains contributions from noted scholars in computer science and electrical engineering from around the globe Provides a broad overview of recent developments in sensor collected intelligence Edited by a team comprised of leading thinkers in big data analytics