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Job Scheduling Strategies for Parallel Processing

26th Workshop, JSSPP 2023, St. Petersburg, FL, USA, May 19, 2023, Revised Selected Papers

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Dalibor Klusáček

    1. CESNET, Prague, Czech Republic

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    You can also search for this editor in PubMed   Google Scholar

  2. Julita Corbalán

    1. Barcelona Supercomputing Center, Barcelona, Spain

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    You can also search for this editor in PubMed   Google Scholar

  3. Gonzalo P. Rodrigo

    1. Apple, Cupertino, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14283)

Included in the following conference series:

Conference proceedings info: JSSPP 2023.

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About this book

This book constitutes the thoroughly refereed post-conference proceedings of the 26th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2023, held in St. Petersburg, FL, USA, during May 19, 2023.



The 8 full papers and one keynote paper included in this book were carefully reviewed and selected from 14 submissions. The volume contains two sections: keynote and technical papers.

Keywords

Table of contents (9 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Keynote

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Architecture of the Slurm Workload Manager

      • Morris A. Jette, Tim Wickberg
      Pages 3-23

  3. Technical Papers

    1. Front Matter

      Pages 25-25
      Download chapter PDF

    2. Asynchronous Execution of Heterogeneous Tasks in ML-Driven HPC Workflows

      • Vincent R. Pascuzzi, Ozgur O. Kilic, Matteo Turilli, Shantenu Jha
      Pages 27-45

    3. Memory-Aware Latency Prediction Model for Concurrent Kernels in Partitionable GPUs: Simulations and Experiments

      • Alessio Masola, Nicola Capodieci, Roberto Cavicchioli, Ignacio Sanudo Olmedo, Benjamin Rouxel
      Pages 46-73

    4. Stragglers in Distributed Matrix Multiplication

      • Roy Nissim, Oded Schwartz
      Pages 74-96

    5. Optimization Metrics for the Evaluation of Batch Schedulers in HPC

      • Robin Boëzennec, Fanny Dufossé, Guillaume Pallez
      Pages 97-115

    6. An Experimental Analysis of Regression-Obtained HPC Scheduling Heuristics

      • Lucas Rosa, Danilo Carastan-Santos, Alfredo Goldman
      Pages 116-136

    7. An Efficient Approach Based on Graph Neural Networks for Predicting Wait Time in Job Schedulers

      • Tomoe Kishimoto, Tomoaki Nakamura
      Pages 137-154

    8. Evaluating the Potential of Coscheduling on High-Performance Computing Systems

      • Jason Hall, Arjun Lathi, David K. Lowenthal, Tapasya Patki
      Pages 155-172

    9. Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation

      • Luis de la Torre, Mahantesh Halappanavar
      Pages 173-192

  4. Back Matter

    Pages 193-193
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Other volumes

  1. Job Scheduling Strategies for Parallel Processing

Editors and Affiliations

  • CESNET, Prague, Czech Republic

    Dalibor Klusáček

  • Barcelona Supercomputing Center, Barcelona, Spain

    Julita Corbalán

  • Apple, Cupertino, USA

    Gonzalo P. Rodrigo

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