Machine Learning-assisted Computational Steering of Large-scale Scientific Simulations
Document Type
Conference Proceeding
Publication Date
1-1-2021
Abstract
Next-generation scientific applications in various fields are experiencing a rapid transition from traditional experiment-based methodologies to large-scale computation-intensive simulations featuring complex numerical modeling with a large number of tunable parameters. Such model-based simulations generate colossal amounts of data, which are then processed and analyzed against experimental or observation data for parameter calibration and model validation. The sheer volume and complexity of such data, the large model-parameter space, and the intensive computation make it practically infeasible for domain experts to manually configure and tune hyperparameters for accurate modeling in complex and distributed computing environments. This calls for an online computational steering service to enable real-time multi-user interaction and automatic parameter tuning. Towards this goal, we design and develop a generic steering framework based on Bayesian Optimization (BO) and conduct theoretical performance analysis of the steering service. We present a case study with the Weather Research and Forecast (WRF) model, which illustrates the performance superiority of the BO-based tuning over other heuristic methods and manual settings of domain experts using regret analysis.
Identifier
85124161316 (Scopus)
ISBN
[9781665435741]
Publication Title
19th IEEE International Symposium on Parallel and Distributed Processing with Applications 11th IEEE International Conference on Big Data and Cloud Computing 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications Ispa Bdcloud Socialcom Sustaincom 2021
External Full Text Location
https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00138
First Page
984
Last Page
992
Grant
CNS-1828123
Fund Ref
National Science Foundation
Recommended Citation
Liu, Wuji; Ye, Qianwen; Wu, Chase Q.; Liu, Yangang; Zhou, Xin; and Shan, Yunpeng, "Machine Learning-assisted Computational Steering of Large-scale Scientific Simulations" (2021). Faculty Publications. 4586.
https://digitalcommons.njit.edu/fac_pubs/4586
