High Performance Big Data Computing
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High Performance Big Data Computing
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Author : Dhabaleswar K. Panda
language : en
Publisher: MIT Press
Release Date : 2022-08-02
High Performance Big Data Computing written by Dhabaleswar K. Panda and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-02 with Computers categories.
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
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Author : Pethuru Raj
language : en
Publisher: Springer
Release Date : 2015-10-16
High Performance Big Data Analytics written by Pethuru Raj and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-16 with Computers categories.
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.
Big Data And High Performance Computing
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Author : L. Grandinetti
language : en
Publisher: IOS Press
Release Date : 2015-10-20
Big Data And High Performance Computing written by L. Grandinetti and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-20 with Computers categories.
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
Conquering Big Data With High Performance Computing
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Author : Ritu Arora
language : en
Publisher: Springer
Release Date : 2016-09-16
Conquering Big Data With High Performance Computing written by Ritu Arora and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-16 with Computers categories.
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.
High Performance Computing For Big Data
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Author : Chao Wang
language : en
Publisher: CRC Press
Release Date : 2017-10-16
High Performance Computing For Big Data written by Chao Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Computers categories.
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.
High Performance Modelling And Simulation For Big Data Applications
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Author : Joanna Kołodziej
language : en
Publisher: Springer
Release Date : 2019-03-25
High Performance Modelling And Simulation For Big Data Applications written by Joanna Kołodziej and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-25 with Computers categories.
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.
Big Data Computing
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Author : Tanvir Habib Sardar
language : en
Publisher: CRC Press
Release Date : 2024-02-27
Big Data Computing written by Tanvir Habib Sardar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-27 with Computers categories.
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.
New Frontiers In High Performance Computing And Big Data
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Author : G. Fox
language : en
Publisher: IOS Press
Release Date : 2017-11-14
New Frontiers In High Performance Computing And Big Data written by G. Fox and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-14 with Computers categories.
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.
Big Data And Hpc Ecosystem And Convergence
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Author : L. Grandinetti
language : en
Publisher: IOS Press
Release Date : 2018-08-22
Big Data And Hpc Ecosystem And Convergence written by L. Grandinetti and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-22 with Computers categories.
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.
Big Data Platforms And Applications
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Author : Florin Pop
language : en
Publisher: Springer Nature
Release Date : 2021-09-28
Big Data Platforms And Applications written by Florin Pop and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-28 with Computers categories.
This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge. The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.