Scalable Data Management of the Uintah Simulation Framework for Next-Generation Engineering Problems with Radiation

Sidharth Kumar, Alan Humphrey, Will Usher, Steve Petruzza Brad Peterson, John A. Schmidt, Derek Harris, Ben Isaac, Jeremy Thornock, Todd Harman, Valerio Pascucci, and Martin Berzins
In Supercomputing Frontiers, 2018

Abstract

The need to scale next-generation industrial engineering problems to the largest computational platforms presents unique challenges. This paper focuses on data management related problems faced by the Uintah simulation framework at a production scale of 260K processes. Uintah provides a highly scalable asynchronous many-task runtime system, which in this work is used for the modeling of a 1000 megawatt electric (MWe) ultra-supercritical (USC) coal boiler. At 260K processes, we faced both parallel I/O and visualization related challenges, e.g., the default file-per-process I/O approach of Uintah did not scale on Mira. In this paper we present a simple to implement, restructuring based parallel I/O technique. We impose a restructuring step that alters the distribution of data among processes. The goal is to distribute the dataset such that each process holds a larger chunk of data, which is then written to a file independently. This approach finds a middle ground between two of the most common parallel I/O schemes–file per process I/O and shared file I/O–in terms of both the total number of generated files, and the extent of communication involved during the data aggregation phase. To address scalability issues when visualizing the simulation data, we developed a lightweight renderer using OSPRay, which allows scientists to visualize the data interactively at high quality and make production movies. Finally, this work presents a highly efficient and scalable radiation model based on the sweeping method, which significantly outperforms previous approaches in Uintah, like discrete ordinates. The integrated approach allowed the USC boiler problem to run on 260K CPU cores on Mira.

BibTeX

@incollection{kumar_scalable_2018,
title = {Scalable {Data} {Management} of the {Uintah} {Simulation} {Framework} for {Next}-{Generation} {Engineering} {Problems} with {Radiation}},
volume = {10776},
isbn = {978-3-319-69952-3 978-3-319-69953-0},
booktitle = {Supercomputing {Frontiers}},
publisher = {Springer International Publishing},
author = {Kumar, Sidharth and Humphrey, Alan and Usher, Will and Petruzza, Steve and Peterson, Brad and Schmidt, John A. and Harris, Derek and Isaac, Ben and Thornock, Jeremy and Harman, Todd and Pascucci, Valerio and Berzins, Martin},
editor = {Yokota, Rio and Wu, Weigang},
year = {2018},
doi = {10.1007/978-3-319-69953-0_13},
pages = {219--240},
}