%0 Journal Article %J Parallel Computing %D 2022 %T OpenMP application experiences: Porting to accelerated nodes %A Bak, Seonmyeong %A Bertoni, Colleen %A Boehm, Swen %A Budiardja, Reuben %A Chapman, Barbara M. %A Doerfert, Johannes %A Eisenbach, Markus %A Finkel, Hal %A Hernandez, Oscar %A Huber, Joseph %A Iwasaki, Shintaro %A Kale, Vivek %A Kent, Paul R.C. %A Kwack, JaeHyuk %A Lin, Meifeng %A Luszczek, Piotr %A Luo, Ye %A Pham, Buu %A Pophale, Swaroop %A Ravikumar, Kiran %A Sarkar, Vivek %A Scogland, Thomas %A Tian, Shilei %A Yeung, P.K. %X As recent enhancements to the OpenMP specification become available in its implementations, there is a need to share the results of experimentation in order to better understand the OpenMP implementation’s behavior in practice, to identify pitfalls, and to learn how the implementations can be effectively deployed in scientific codes. We report on experiences gained and practices adopted when using OpenMP to port a variety of ECP applications, mini-apps and libraries based on different computational motifs to accelerator-based leadership-class high-performance supercomputer systems at the United States Department of Energy. Additionally, we identify important challenges and open problems related to the deployment of OpenMP. Through our report of experiences, we find that OpenMP implementations are successful on current supercomputing platforms and that OpenMP is a promising programming model to use for applications to be run on emerging and future platforms with accelerated nodes. %B Parallel Computing %V 109 %8 2022-03 %G eng %U https://www.sciencedirect.com/science/article/pii/S0167819121001009 %! Parallel Computing %R 10.1016/j.parco.2021.102856