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CHPC - Research Computing and Data Support for the University

In addition to deploying and operating high performance computational resources and providing advanced user support and training, CHPC serves as an expert team to broadly support the increasingly diverse research computing and data needs on campus. These needs include support for big data, big data movement, data analytics, security, virtual machines, Windows science application servers, protected environments for data mining and analysis of protected health information, and advanced networking.

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News History...

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Scalable Adaptive Algorithms for Next-Generation Multiphase Flow Simulations

By Masado Ishii, Hari Sundar, Kumar Saurabh, Makrand Khanwale, Baskar Ganapathysubramian

University of Utah, Iowa State University 

Multiphase flows -- more specifically, two-phase flows, where one fluid interacts with another fluid and are ubiquitous in natural and engineered systems. Examples include natural phenomena from breaking waves and cloud formation to engineering applications like printing, additive manufacturing, and all types of spraying operations in healthcare and agriculture. High-fidelity modeling of two-phase flows has been an indispensable strategy for understanding, designing, and controlling such phenomena, however this is difficult due to the wide range of spatial and temporal scales, especially under turbulent conditions.

We have developed scalable algorithms to identify the spatial regions of interest in the computational domain where the flow features become comparable to the mesh resolution, i.e., regions where ϵ/r~O(1). This was essential for phenomena exhibiting droplets and fluid filaments, where such targeted resolution is critical for performing cost-effective simulation physics. We also developed octree refinement and coarsening algorithms to accelerate remeshing and decrease the associated overhead, especially for multi-level refinements. This is essential for simulations where the element sizes drop substantially. For instance, in the canonical example of primary jet atomization, element sizes vary by three orders of magnitude to accurately resolve fluid features varying by nine orders of magnitude in volume. This contrasts with existing approaches, where refinement or coarsening of the octrees is done level by level.

We demonstrate the ability of our algorithm, producing one of the highest resolution datasets of primary jet atomization. Initial development and testing and validation of our methods were done on the notchpeak cluster at CHPC. The full-scale production run required over 200,000 node hours on TACC Frontera, is equivalent to 35 trillion grid points on a uniform mesh and is 64x more resolved than the current state-of-the-art simulations.



 

 

 









 



 



 






 

System Status

General Environment

last update: 2024-03-29 07:43:04
General Nodes
system cores % util.
kingspeak 532/972 54.73%
notchpeak 1917/3212 59.68%
lonepeak 3092/3140 98.47%
Owner/Restricted Nodes
system cores % util.
ash 768/1104 69.57%
notchpeak 6850/18300 37.43%
kingspeak 2180/5308 41.07%
lonepeak 336/416 80.77%

Protected Environment

last update: 2024-03-29 07:40:04
General Nodes
system cores % util.
redwood 441/616 71.59%
Owner/Restricted Nodes
system cores % util.
redwood 2116/5980 35.38%


Cluster Utilization

Last Updated: 2/20/24