@inproceedings{d9dd7c42420f423499df1ffb5ac102c1,
title = "Static Graphs for Coding Productivity in OpenACC",
abstract = "The main contribution of this work is to increase the coding productivity for GPU programming by using the concept of Static Graphs. To do so, we have combined the new CUDA Graph API with the OpenACC programming model. We use as test cases a well-known and widely used problems in HPC and AI: the Particle Swarm Optimization. We complement the OpenACC functionality with the use of CUDA Graph, achieving accelerations of more than one order of magnitude, and a performance very close to a reference and optimized CUDA code. Finally, we propose a new specification to incorporate the concept of Static Graphs into the OpenACC specification.",
keywords = "Coding Productivity, Data Dependencies, OpenACC, Particle Swarm Optimization, Static Graph, Tasking",
author = "Leonel Toledo and Pedro Valero-Lara and Jeffrey Vetter and Pena, {Antonio J.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 28th IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2021 ; Conference date: 17-12-2021 Through 18-12-2021",
year = "2021",
doi = "10.1109/HiPC53243.2021.00050",
language = "English",
series = "Proceedings - 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics, HiPC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "364--369",
booktitle = "Proceedings - 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics, HiPC 2021",
}