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: Artificial Intelligence and Hardware Accelerators
  name:
    name part: Mishra, Ashutosh.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Cha, Jaekwang.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Park, Hyunbin.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Kim, Shiho.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2023
    edition: 1st ed. 2023.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (VII, 357 pages 237 illustrations, 202 illustrations in color)
  abstract: This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers' journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators.
  table of contents: Introduction -- AI Hardware Accelerators -- AI Accelerators for Standalone Compute -- AI Accelerators for Servers and Cloud Applications -- AI Accelerators for Configurable Hardware -- Hardware Architecture for Smartphones -- Software and Benchmark for Smartphones -- Hardware Accelerators for Autonomous Vehicles -- Hardware Accelerators in Embedded Systems -- Processing-In-Memory based Hardware Accelerator -- Emerging CNN Hardware Architectures for Energy-efficient AI -- Neuromorphic Hardware Accelerators.
  note: edited by Ashutosh Mishra, Jaekwang Cha, Hyunbin Park, Shiho Kim.
  subject:
    topic: Electronic circuits
  subject:
    topic: Cooperating objects (Computer systems)
  subject:
    topic: Artificial intelligence
  subject:
    topic: Electronic Circuits and Systems
  subject:
    topic: Cyber-Physical Systems
  subject:
    topic: Artificial Intelligence
  classification: TK7867-7867.5
  classification: 621.3815
  related item:
    title info:
      title: Springer Nature eBook
  identifier: 9978-3-031-22170-5
  identifier: 9783031221705
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 230315
    record change date: 20240805182146.5
    record identifier: in00004656183