Euro-Par 2023: Parallel Processing [electronic resource] : 29th International Conference on Parallel and Distributed Computing, Limassol, Cyprus, August 28 – September 1, 2023, Proceedings /

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Material type: Text

TextSeries: Lecture Notes in Computer Science ; 14100Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023Description: XLV, 743 p. 278 illus., 233 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783031396984

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

005.1 23

LOC classification:

QA76.758

Online resources:

Click here to access online

Contents:

Programming, Compilers and Performance -- Scheduling, Resource Management, Cloud, Edge Computing, and Workflows -- Architectures and Accelerators -- Data Analytics, AI, and Computational Science -- Theory and Algorithms -- Multidisciplinary, and Domain-Specific and Applied Parallel and Distributed Computing.

In: Springer Nature eBookSummary: This book constitutes the proceedings of the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023, held in Limassol, Cyprus, in August/September 2023. The 49 full papers presented in this volume were carefully reviewed and selected from 164 submissions. They are covering the following topics: programming, compilers and performance; scheduling, resource management, cloud, edge computing, and workflows; architectures and accelerators; data analytics, AI, and computational science; theory and algorithms; multidisciplinary, and domain-specific and applied parallel and distributed computing.

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This book constitutes the proceedings of the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023, held in Limassol, Cyprus, in August/September 2023. The 49 full papers presented in this volume were carefully reviewed and selected from 164 submissions. They are covering the following topics: programming, compilers and performance; scheduling, resource management, cloud, edge computing, and workflows; architectures and accelerators; data analytics, AI, and computational science; theory and algorithms; multidisciplinary, and domain-specific and applied parallel and distributed computing.

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