Abstract
The traditional workflow in a high performance computing (HPC) simulation is to prepare the application's input, run the simulation, and visualize the simulation results in a post-processing step. By performing these steps simultaneously, significant development and testing time can be saved. Computational steering provides the capability to direct or re-direct the progress of an HPC application at run-time by modifying application-defined control parameters using a steering client application. In this paper, we discuss a computational steering framework for the Blue Gene/Q system that provides an innovative solution and an easy-to-use platform, which allows user(s) to connect to and interact with running application(s) in real-time from native desktop steering applications and/or mobile devices. This framework uses RealityGrid as the underlying steering library and adds several enhancements to the library to enable steering support for the Blue Gene systems. The Blue Gene supercomputer presents special challenges for remote access because the compute nodes reside on private networks. This paper discusses an implemented solution for remote steering of simulation applications running on a high performance computer system and describes the implementation challenges.
| Original language | English (US) |
|---|---|
| Title of host publication | 23rd High Performance Computing Symposium, HPC 2015, Part of the 2015 Spring Simulation Multi-Conference, SpringSim 2015 |
| Publisher | The Society for Modeling and Simulation Internationalwww.scs.org |
| Pages | 202-209 |
| Number of pages | 8 |
| State | Published - Jan 1 2015 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2022-06-29Acknowledgements: This work was supported by a joint collaboration between IBM T. J. Watson Research Center and King Abdullah University of Science and Technology (KAUST). We would like to thank D. Kaushik of Supercomputer Laboratory at KAUST, and J. Sexton of IBM T. J. Watson Research Center who led this collaboration.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.