SIGMETRICS/Performance 2012 : Proceedings of the 2012 ACM SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, June 11-15, 2012, London, UK. PDF Download
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Author: Peter Harrison
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Peter Harrison
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author:
Publisher:
ISBN:
Category : Computer networks
Languages : en
Pages : 436
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Peter Harrison
Publisher:
ISBN: 9781450310970
Category : Computer networks
Languages : en
Pages : 436
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Book Description
Author: ACM-Sigmetrics
Publisher: ACM Press
ISBN: 9781450317337
Category : Computers
Languages : en
Pages : 452
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Author: Peter Harrison
Publisher:
ISBN: 9781450315029
Category :
Languages : en
Pages :
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SIGMETRICS '12:ACM SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Jun 11, 2012-Jun 15, 2012 London, United Kingdom. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Author: Peter Harrison
Publisher:
ISBN: 9781450310970
Category : Computer networks
Languages : en
Pages : 436
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Book Description
Author: Shuguang Cui
Publisher: Cambridge University Press
ISBN: 1316445275
Category : Technology & Engineering
Languages : en
Pages : 459
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Book Description
Utilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data over large systems, making it essential reading for graduate students, scientific researchers and industry practitioners alike.
Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 1498768083
Category : Business & Economics
Languages : en
Pages : 489
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Book Description
From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.
Author: Jeffrey Nichols
Publisher: Springer Nature
ISBN: 3030633934
Category : Computers
Languages : en
Pages : 555
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Book Description
This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
