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.
If you are new to CHPC, the best place to start to get more information on CHPC resources and policies is our Getting Started page.
Upcoming Events:
CHPC Downtime: Tuesday March 5 starting at 7:30am
Posted February 8th, 2024
Two upcoming security related changes
Posted February 6th, 2024
Allocation Requests for Spring 2024 are Due March 1st, 2024
Posted February 1st, 2024
CHPC ANNOUNCEMENT: Change in top level home directory permission settings
Posted December 14th, 2023
CHPC Spring 2024 Presentation Schedule Now Available
CHPC PE DOWNTIME: Partial Protected Environment Downtime -- Oct 24-25, 2023
Posted October 18th, 2023
CHPC INFORMATION: MATLAB and Ansys updates
Posted September 22, 2023
CHPC SECURITY REMINDER
Posted September 8th, 2023
CHPC is reaching out to remind our users of their responsibility to understand what the software being used is doing, especially software that you download, install, or compile yourself. Read More...News History...
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
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
General Nodes | ||
---|---|---|
system | cores | % util. |
redwood | 441/616 | 71.59% |
Owner/Restricted Nodes | ||
system | cores | % util. |
redwood | 2116/5980 | 35.38% |