OpenMP: Balancing Productivity and Performance Portability: 21st International Workshop on OpenMP, IWOMP...

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Yonghong Yan Michael Klemm

OpenMP

Balancing Productivity and Performance Portability: 21st International Workshop on OpenMP, IWOMP...

Yonghong Yan, Michael Klemm, Bronis R. de Supinski , Erik Saule

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English

Springer Nature Switzerland AG
29 September 2025

Computer hardware; Compilers; Systems analysis & design; Expert & knowledge-based systems

Series: Lecture Notes in Computer Science

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.

Edited by: Yonghong Yan, Michael Klemm, Bronis R. de Supinski, Erik Saule, Jannis Klinkenberg
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783032063427
ISBN 10: 3032063426
Series: Lecture Notes in Computer Science
Pages: 227
Publication Date: 29 September 2025
Audience: College/higher education , Professional and scholarly , Further / Higher Education , Undergraduate
Format: Paperback
Publisher's Status: Active

.- 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 Instinct™ 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.