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Herausgeber: 
  • Narayan Desai
  • Walfredo Cirne
  • Dalibor Klusá¿ek
  • Job Scheduling Strategies for Parallel Processing: 21st International Workshop, JSSPP 2017, Orlando, FL, USA, June 2, 2017, Revised Selected Papers 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Februar 2018  
    Genre:  EDV / Informatik 
     
    Architecture, Computer / C / Computer architecture & logic design / computer science / Computer System Implementation / Expert systems / knowledge-based systems / Logic Design / Microprocessors / Operating systems / Processor Architectures / Software Engineering / Software Engineering/Programming and Operating Systems / Special Purpose and Application-Based Systems / Special purpose computers / Systems analysis & design
    ISBN:  9783319773971 
    EAN-Code: 
    9783319773971 
    Verlag:  Springer International Publishing 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #10773 - Lecture Notes in Computer Science
    Theoretical Computer Science and General Issues  
    Dimensionen:  H 235 mm / B 155 mm / D 12 mm 
    Gewicht:  312 gr 
    Seiten:  200 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book constitutes the thoroughly refereed post-conference proceedings of the 21st International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2017, held in Orlando, FL, USA, in June 2017.
    The 10 revised full papers presented in this book were carefully reviewed and selected from 20 submissions. The papers cover topics in the fields of design and evaluation of new scheduling approaches; performance evaluation of scheduling approaches; workloads; consideration of additional constraints in scheduling systems; scaling and composition of very large scheduling systems; cloud provider issues; interaction between schedulers on different levels; interaction between applications/workloads; experience reports from production systems or large scale compute campaigns. 
      



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