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

Journal Article · Thu Mar 29 00:00:00 EDT 2018 · Lecture Notes in Computer Science

DOI:https://doi.org/10.1007/978-3-319-69953-0· OSTI ID:1582441

Kumar, Sidharth ^[1]; Humphrey, Alan ^[2]; Usher, Will ^[2]; Petruzza, Steve ^[2]; Peterson, Brad ^[2]; Schmidt, John A ^[2]; Harris, Derek ^[3]; Isaac, Ben ^[3]; Thornock, Jeremy ^[3]; Harman, Todd ^[3]; Pascucci, Valerio ^[2]; Berzins, Martin ^[2]

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1. Univ. of Utah, Salt Lake City, UT (United States). Scientific Computing and Imaging Inst.(SCI); University of Utah
2. Univ. of Utah, Salt Lake City, UT (United States). Scientific Computing and Imaging Inst.(SCI)
3. Univ. of Utah, Salt Lake City, UT (United States). Inst. for Clean and Secure Energy

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.

• Research Organization: Univ. of Utah, Salt Lake City, UT (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC02-06CH11357; NA0002375
• OSTI ID: 1582441
• Journal Information: Lecture Notes in Computer Science, Journal Name: Lecture Notes in Computer Science Vol. 10776; ISSN 0302-9743
• Publisher: Springer
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
Data Management
Uintah
Asynchronous Many-Task Runtime Systems
Visualization