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Data Management on New Hardware: 7th International Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016 and 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, New Delhi, India, September 1, 2016, Revised Selected Papers

Data Management on New Hardware: 7th International Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016 and 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, New Delhi, India, September 1, 2016, Revised Selected Papers
Kataloginformation
Feldname Details
Vorliegende Sprache eng
ISBN 978-3-319-56110-3
Name Blanas, Spyros
Bordawekar, Rajesh ¬[Hrsg.]¬
Name ANZEIGE DER KETTE Bordawekar, Rajesh ¬[Hrsg.]¬
Name Lahiri, Tirthankar
Levandoski, Justin
Pavlov, Andrew
T I T E L Data Management on New Hardware
Zusatz zum Titel 7th International Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016 and 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, New Delhi, India, September 1, 2016, Revised Selected Papers
Verlagsort Cham
Verlag Springer
Erscheinungsjahr 2017
2017
Umfang Online-Ressource (VII, 167 p. 99 illus, online resource)
Reihe Lecture Notes in Computer Science ; 10195
Lecture notes in computer science
Band 10195
Titelhinweis Druckausg.ISBN: 978-3-319-56110-3
Printed editionISBN: 978-3-319-56110-3
ISBN ISBN 978-3-319-56111-0
Klassifikation UMT
UN
COM021000
005.74
QA76.9.D3
Kurzbeschreibung This book contains selected papers from the 7th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, ADMS 2016, and the 4th International Workshop on In-Memory Data Management and Analytics, IMDM 2016, held in New Dehli, India, in September 2016. The joint Workshops were co-located with VLDB 2016. The 9 papers presented were carefully reviewed and selected from 18 submissions. They investigate opportunities in accelerating analytics/data management systems and workloads (including traditional OLTP, data warehousing/OLAP, ETL streaming/real-time, business analytics, and XML/RDF processing) running memory-only environments, using processors (e.g. commodity and specialized multi-core, GPUs and FPGAs, storage systems (e.g. storage-class memories like SSDs and phase-change memory), and hybrid programming models like CUDA, OpenCL, and Open ACC. The papers also explore the interplay between overall system design, core algorithms, query optimization strategies, programming approaches, performance modeling and evaluation, from the perspective of data management applications
2. Kurzbeschreibung Accelerating analytics/data management systems -- Workloads (including traditional OLTP, data warehousing/OLAP, ETL streaming/real-time, business analytics, and XML/RDF processing) -- Running memory-only environments, using processors (e.g. commodity and specialized multi-core, GPUs and FPGAs, storage systems (e.g. storage-class memories like SSDs and phase-change memory) -- Hybrid programming models like CUDA, OpenCL, and Open ACC -- Interplay between overall system design, core algorithms, query optimization strategies, programming approaches, performance modeling and evaluation, from the perspective of data management applications
1. Schlagwortkette Datenmanagement
ANZEIGE DER KETTE Datenmanagement
SWB-Titel-Idn 486675610
Signatur Springer E-Book
Bemerkungen Elektronischer Volltext - Campuslizenz
Elektronische Adresse $uhttp://dx.doi.org/10.1007/978-3-319-56111-0
Internetseite / Link Volltext
Kataloginformation500248046 Datensatzanfang . Kataloginformation500248046 Seitenanfang .
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