A Co-Design Study Of Fusion Whole Device Modeling Using Code Coupling
Jong Youl Choi, Jeremy S. Logan, Kshitij R. Mehta, Eric Suchyta, William F. Godoy, Nick Thompson, Lipeng Wan, Jieyang Chen, Norbert Podhorszki, Matthew Wolf, Scott Klasky, J. Dominski, C. S. Chang · 2019
Complex workflows consisting of multiple simulation and analysis codes running concurrently through in-memory coupling is becoming popular due to inherent advantages in online management of large-scale data, resilience, and the code development process. However, orchestrating such a multi-application workflow to efficiently utilize resources on a heterogeneous architecture is challenging. In this paper, we present our results with running the Fusion Whole Device Modeling benchmark workflow on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory. We explore various resource distribution and process placement mechanisms, including sharing compute nodes between processes from separate applications. We show that fine-grained process placement can have a significant impact towards efficient utilization of the compute power of a node on Summit, and conclude that sophisticated tools for performing co-design studies of multi-application workflows can play an important role towards efficient orchestration of such workflows.