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OpenMP: Enabling Massive Node-Level Parallelism

17th International Workshop on OpenMP, IWOMP 2021, Bristol, UK, September 14–16, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Simon McIntosh-Smith

    1. University of Bristol, Bristol, UK

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    You can also search for this editor in PubMed   Google Scholar

  2. Bronis R. de Supinski

    1. Lawrence Livermore National Laboratory, Livermore, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Jannis Klinkenberg

    1. RWTH Aachen University, Aachen, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12870)

Part of the book sub series: Programming and Software Engineering (LNPSE)

Included in the following conference series:

Conference proceedings info: IWOMP 2021.

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Table of contents (15 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Synchronization and Data

    1. Front Matter

      Pages 1-1
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    2. Improving Speculative taskloop in Hardware Transactional Memory

      • Juan Salamanca, Alexandro Baldassin
      Pages 3-17

    3. Vectorized Barrier and Reduction in LLVM OpenMP Runtime

      • Muhammad Nufail Farooqi, Miquel Pericàs
      Pages 18-32

  3. Tasking Extensions I

    1. Front Matter

      Pages 33-33
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    2. Enhancing OpenMP Tasking Model: Performance and Portability

      • Chenle Yu, Sara Royuela, Eduardo Quiñones
      Pages 35-49

    3. OpenMP Taskloop Dependences

      • Marcos Maroñas, Xavier Teruel, Vicenç Beltran
      Pages 50-64

  4. Applications

    1. Front Matter

      Pages 65-65
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    2. Outcomes of OpenMP Hackathon: OpenMP Application Experiences with the Offloading Model (Part I)

      • Barbara Chapman, Buu Pham, Charlene Yang, Christopher Daley, Colleen Bertoni, Dhruva Kulkarni et al.
      Pages 67-80

    3. Outcomes of OpenMP Hackathon: OpenMP Application Experiences with the Offloading Model (Part II)

      • Barbara Chapman, Buu Pham, Charlene Yang, Christopher Daley, Colleen Bertoni, Dhruva Kulkarni et al.
      Pages 81-95

    4. An Empirical Investigation of OpenMP Based Implementation of Simplex Algorithm

      • Arkaprabha Banerjee, Pratvi Shah, Shivani Nandani, Shantanu Tyagi, Sidharth Kumar, Bhaskar Chaudhury
      Pages 96-110

    5. Task Inefficiency Patterns for a Wave Equation Solver

      • Holger Schulz, Gonzalo Brito Gadeschi, Oleksandr Rudyy, Tobias Weinzierl
      Pages 111-124

  5. Case Studies

    1. Front Matter

      Pages 125-125
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    2. Comparing OpenMP Implementations with Applications Across A64FX Platforms

      • Benjamin Michalowicz, Eric Raut, Yan Kang, Tony Curtis, Barbara Chapman, Dossay Oryspayev
      Pages 127-141

    3. A Case Study of LLVM-Based Analysis for Optimizing SIMD Code Generation

      • Joseph Huber, Weile Wei, Giorgis Georgakoudis, Johannes Doerfert, Oscar Hernandez
      Pages 142-155

  6. Heterogenous Computing and Memory

    1. Front Matter

      Pages 157-157
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    2. Experience Report: Writing a Portable GPU Runtime with OpenMP 5.1

      • Shilei Tian, Jon Chesterfield, Johannes Doerfert, Barbara Chapman
      Pages 159-169

    3. FOTV: A Generic Device Offloading Framework for OpenMP

      • Jose Luis Vazquez, Pablo Sanchez
      Pages 170-182Open Access

    4. Beyond Explicit Transfers: Shared and Managed Memory in OpenMP

      • Brandon Neth, Thomas R. W. Scogland, Alejandro Duran, Bronis R. de Supinski
      Pages 183-194

  7. Tasking Extensions II

    1. Front Matter

      Pages 195-195
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  1. OpenMP: Enabling Massive Node-Level Parallelism

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About this book

This book constitutes the proceedings of the 17th International Workshop on OpenMP, IWOMP 2021, held virtually in September 2021 and hosted by the High Performance Computing research group at the University of Bristol, UK.

The 15 full papers presented in this volume were carefully reviewed and selected for inclusion in this book. The papers are organized in topical sections named: synchronization and data; tasking expansions; applications; case studies; and heterogenous computing and memory.

Chapter ‘FOTV: A Generic Device Offloading Framework for OpenMP’ is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Editors and Affiliations

  • University of Bristol, Bristol, UK

    Simon McIntosh-Smith

  • Lawrence Livermore National Laboratory, Livermore, USA

    Bronis R. de Supinski

  • RWTH Aachen University, Aachen, Germany

    Jannis Klinkenberg

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