OpenMP Kernel Language Extensions for Performance Portable GPU Codes-Reference-Cited by-同舟云学术

OpenMP Kernel Language Extensions for Performance Portable GPU Codes

Published:2023-11-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
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Author:

Tian Shilei¹^ORCID,Scogland Tom²^ORCID,Chapman Barbara³^ORCID,Doerfert Johannes²^ORCID

Affiliation:

1. Stony Brook University, United States of America

2. Lawrence Livermore National Laboratory, United States of America

3. Stony Brook University, United States of America and Hewlett Packard Enterprise, United States of America

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624062.3624164

Reference28 articles.

1. AMD. 2023. HIP Documentation. https://rocm.docs.amd.com/projects/HIP/en/latest/ AMD. 2023. HIP Documentation. https://rocm.docs.amd.com/projects/HIP/en/latest/

2. RAJA: Portable Performance for Large-Scale Scientific Applications

3. Carleton DeTar , Steven Gottlieb , Ruizi Li , and Doug Toussaint . 2017. MILC Code Performance on High End CPU and GPU Supercomputer Clusters. arXiv 175 (11 2017 ), 1–8. arxiv:1712.00143 Carleton DeTar, Steven Gottlieb, Ruizi Li, and Doug Toussaint. 2017. MILC Code Performance on High End CPU and GPU Supercomputer Clusters. arXiv 175 (11 2017), 1–8. arxiv:1712.00143

4. Breaking the Vendor Lock

5. Co-Designing an OpenMP GPU Runtime and Optimizations for Near-Zero Overhead Execution

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