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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 / Spyros Blanas, Rajesh Bordawekar, Tirthankar Lahiri, Justin Levandoski, Andrew Pavlo (eds).

International Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage Architectures (7th : 2016 : New Delhi, India); Blanas, Spyros, editor.; Bordawekar, Rajesh, editor.; Lahiri, Tirthankar, editor.; Levandoski, Justin, editor.; Pavlo, Andrew, editor.; IMDM (Workshop) (4th : 2016 : New Delhi, India), jointly held conference.
2017
QA76.9.M45
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Title
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 / Spyros Blanas, Rajesh Bordawekar, Tirthankar Lahiri, Justin Levandoski, Andrew Pavlo (eds).
Meeting Name
International Workshop on Accelerating Data Analysis and Data Management Systems Using Modern Processor and Storage Architectures (7th : 2016 : New Delhi, India)
ISBN
9783319561110 (electronic book)
3319561111 (electronic book)
9783319561103
3319561103
DOI
https://doi.org/10.1007/978-3-319-56111-0
Published
Cham, Switzerland : Springer, 2017.
Language
English
Description
1 online resource (vii, 167 pages) : illustrations.
Item Number
10.1007/978-3-319-56111-0 doi
Call Number
QA76.9.M45
Dewey Decimal Classification
005.4/35
Summary
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.
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Includes author index.
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Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 4, 2017).
Added Author
Blanas, Spyros, editor.
Bordawekar, Rajesh, editor.
Lahiri, Tirthankar, editor.
Levandoski, Justin, editor.
Pavlo, Andrew, editor.
Added Meeting Name
IMDM (Workshop) (4th : 2016 : New Delhi, India), jointly held conference.
Series
Lecture notes in computer science ; 10195.
LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI.
Available in Other Form
Print version: 3319561103
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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.

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