Advancing OpenMP for Future Accelerators (eBook, PDF)

20th International Workshop on OpenMP, IWOMP 2024, Perth, WA, Australia, September 23-25, 2024, Proceedings
Redaktion: Espinosa, Alexis; Klinkenberg, Jannis; Cytowski, Maciej; De Supinski, Bronis R.; Klemm, Michael

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 20th International Workshop on OpenMP: Advancing OpenMP for Future Accelerators, IWOMP 2024, in Perth, WA, Australia, during September 23-25, 2024.

The 14 full papers presented in this book were carefully reviewed and selected from 16 submissions. They are grouped into the following topics: current and future openMP optimization; targeting more devices; best practices; tools; and simplifying parallelization.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 226
• Erscheinungstermin: 18. September 2024
• Englisch
• ISBN-13: 9783031725678
• Artikelnr.: 72242476

Inhaltsangabe

.- Current and Future OpenMP Optimization.

.- Towards Locality-Aware Host-to-Device Offloading in OpenMP.

.- Performance Porting the ExaStar Multi-physics App Thornado On Heterogeneous Systems - A Fortran-OpenMP Code-base Evaluation.

.- Event-Based OpenMP Tasks for Time-Sensitive GPU-Accelerated Systems.

.- Targeting More Devices.

.- Integrating Multi-FPGA Acceleration to OpenMP Distributed Computing.

.- Towards a Scalable and Efficient PGAS-based Distributed OpenMP.

.- Multilayer Multipurpose Caches for OpenMP Target Regions on FPGAs.

.- Best Practices.

.- Survey of OpenMP Practice in General Open Source Software.

.- CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations.

.- Evaluation of Directive-based Programming Models for Stencil Computation on Current GPGPU Architectures.

.- Tools.

.- Finding Equivalent OpenMP Fortran and C/C++ Code Snippets Using Large Language Models.

.- Visualizing Correctness Issues in OpenMP Programs.

.- Developing an Interactive OpenMP Programming Book with Large Language Models.

.- Simplifying Parallelization.

.- Automatic Parallelization and OpenMP Offloading of Fortran Array Notation.

.- Detrimental Task Execution Patterns in Mainstream OpenMP Runtimes.