rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data Management on New Hardware
    sub title: 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
  name:
    name part: Blanas, Spyros.
    role:
      role term: editor.
  name:
    name part: Bordawekar, Rajesh.
    role:
      role term: editor.
  name:
    name part: Lahiri, Tirthankar.
    role:
      role term: editor.
  name:
    name part: Levandoski, Justin.
    role:
      role term: editor.
  name:
    name part: Pavlo, Andrew.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VII, 167 p. 99 illus. online resource.
  abstract: 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.
  table of contents: 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.
  note: edited by Spyros Blanas, Rajesh Bordawekar, Tirthankar Lahiri, Justin Levandoski, Andrew Pavlo.
  subject:
    topic: Computer science
  subject:
    topic: Computer communication systems
  subject:
    topic: Software engineering
  subject:
    topic: Data structures (Computer science)
  subject:
    topic: Database management
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Computer Science
  subject:
    topic: Database Management
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Software Engineering
  subject:
    topic: Data Storage Representation
  classification: QA76.9.D3
  classification: 005.74
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 10195
  identifier: 9783319561110
  identifier: http://dx.doi.org/10.1007/978-3-319-56111-0
  record info:
    record creation date: 170322
    record change date: 20170322043250.0
    record identifier: 978-3-319-56111-0