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  • OpenMP: Balancing Productivity and Performance Portability: 21st International Workshop on OpenMP, IWOMP 2025, Charlotte, NC, USA, October 1-3, 2025 Proceedings

    OpenMP: Balancing Productivity and Performance Portability by Yan, Yonghong; Klemm, Michael; de Supinski, Bronis R.;

    21st International Workshop on OpenMP, IWOMP 2025, Charlotte, NC, USA, October 1-3, 2025 Proceedings

    Series: Lecture Notes in Computer Science;

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    Product details:

    • Publisher Springer Nature Switzerland
    • Date of Publication 29 September 2025

    • ISBN 9783032063427
    • Binding Paperback
    • No. of pages227 pages
    • Size 235x155 mm
    • Language English
    • Illustrations X, 227 p. 79 illus., 64 illus. in color.
    • 666

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    Long description:

    This book constitutes the refereed proceedings of the 21st International Workshop on OpenMP, IWOMP 2025, in Charlotte, NC, USA, during October 1 – October 3, 2025

    The 14 full papers included in this book were carefully reviewed and selected from 19 submissions. They were organized in topical sections as follows:New Directions: Communication and I/O; New Directions: Handling New Constraints and Devices; New Performance and Correctness Tooling; Advanced Capability Evaluation and New Directions: Programming Advances.

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    Table of Contents:

    .- New Directions: Communication and I/O.
    .- Discussion of Device-Device Collective Communication in OpenMP Target Offloading.
    .- OMPCCL: Extending OpenMP with Portable Collective Operations for Multiple Devices.
    .- OpenMP Meets I/O: Portable and Runtime-Managed File Tasks.
    .- New Directions: Handling New Constraints and Devices.
    .- Parallelizing Irregular DOACROSS Loops Using ChatGPT and Transactional Memory in OpenMP.
    .- OpenMP-RT: Pragma Support for Scheduling Periodic Real-Time Tasks.
    .- OpenMP-Q: Quantum Task Offloading in OpenMP.
    .- New Performance and Correctness Tooling.
    .- Profile Generation for GPU Targets.
    .- Data Race Satisfiability on Array Elements.
    .- Predicting Performance for OpenMP GPU Parameter Choices.
    .- Advanced Capability Evaluation.
    .- Evaluating LLVM OpenMP Offload Optimizations on NVIDIA GH200 Grace Hopper Superchip and AMD InstinctTM MI300A Accelerator Architectures.
    .- Evaluating OpenMP on Aurora’s Intel GPU Max Series 1550.
    .- Demonstrating OpenMP Offload Performance with the STREAmS-2 Application and the AMD Next-Gen Fortran Compiler.
    .- New Directions: Programming Advances.
    .- ChatPORT: Fine-tuned LLM for Easy Code {PORT}ing.
    .- Programming GPUs with OpenMP and Python.

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