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: PARALLEL AND HIGH-PERFORMANCE COMPUTING IN ARTIFICIAL INTELLIGENCE
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2025
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: Parallel and High-Performance Computing in Artificial Intelligence explores high-performance architectures for data-intensive applications as well as efficient analytical strategies to speed up data processing and applications in automation, machine learning, deep learning, healthcare, bioinformatics, natural language processing (NLP), and vision intelligence.The book's two major themes are high-performance computing (HPC) architecture and techniques and their application in artificial intelligence. Highlights include: HPC use cases, application programming interfaces (APIs), and applications Parallelization techniques HPC for machine learning Implementation of parallel computing with AI in big data analytics HPC with AI in healthcare systems AI in industrial automation Coverage of HPC architecture and techniques includes multicore architectures, parallel-computing techniques, and APIs, as well as dependence analysis for parallel computing. The book also covers hardware acceleration techniques, including those for GPU acceleration to power big data systems.As AI is increasingly being integrated into HPC applications, the book explores emerging and practical applications in such domains as healthcare, agriculture, bioinformatics, and industrial automation. It illustrates technologies and methodologies to boost the velocity and scale of AI analysis for fast discovery. Data scientists and researchers can benefit from the book's discussion on AI-based HPC applications that can process higher volumes of data, provide more realistic simulations, and guide more accurate predictions. The book also focuses on deep learning and edge computing methodologies with HPC and presents recent research on methodologies and applications of HPC in AI.
  note: “An Auerbach Book.”
  subject:
    topic: High performance computing
  subject:
    topic: Artificial intelligence
  subject:
    topic: Superinformatique
  subject:
    topic: Intelligence artificielle
  subject:
    topic: artificial intelligence
  classification: QA76.88
  classification: 004.1/1
  related item:
    identifier: (OCoLC)1464590996
  identifier: 9781040332702
  identifier: 1040332706
  identifier: 9781003425458
  identifier: 1003425453
  identifier: 9781040332726
  identifier: 1040332722
  identifier: 1032540877
  identifier: 9781032540870
  identifier: 9781003425458 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 250411
    record change date: 20250610192223.6
    record identifier: in00005646776
    language of cataloging:
      language term: eng