Multiscale high-order/low-order (HOLO) algorithms and applications
Abstract
Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Institute for Defense Analyses, Alexandria, VA (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1375167
- Alternate Identifier(s):
- OSTI ID: 1397820
- Report Number(s):
- LA-UR-16-23721
Journal ID: ISSN 0021-9991
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Computational Physics
- Additional Journal Information:
- Journal Volume: 330; Journal Issue: C; Journal ID: ISSN 0021-9991
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; Mathematics; High-order/low-order; HOLO; Multiscale algorithms; Implicit timestepping; Communication avoiding algorithms
Citation Formats
Chacon, Luis, Chen, Guangye, Knoll, Dana Alan, Newman, Christopher Kyle, Park, HyeongKae, Taitano, William, Willert, Jeff A., and Womeldorff, Geoffrey Alan. Multiscale high-order/low-order (HOLO) algorithms and applications. United States: N. p., 2016.
Web. doi:10.1016/j.jcp.2016.10.069.
Chacon, Luis, Chen, Guangye, Knoll, Dana Alan, Newman, Christopher Kyle, Park, HyeongKae, Taitano, William, Willert, Jeff A., & Womeldorff, Geoffrey Alan. Multiscale high-order/low-order (HOLO) algorithms and applications. United States. https://doi.org/10.1016/j.jcp.2016.10.069
Chacon, Luis, Chen, Guangye, Knoll, Dana Alan, Newman, Christopher Kyle, Park, HyeongKae, Taitano, William, Willert, Jeff A., and Womeldorff, Geoffrey Alan. Fri .
"Multiscale high-order/low-order (HOLO) algorithms and applications". United States. https://doi.org/10.1016/j.jcp.2016.10.069. https://www.osti.gov/servlets/purl/1375167.
@article{osti_1375167,
title = {Multiscale high-order/low-order (HOLO) algorithms and applications},
author = {Chacon, Luis and Chen, Guangye and Knoll, Dana Alan and Newman, Christopher Kyle and Park, HyeongKae and Taitano, William and Willert, Jeff A. and Womeldorff, Geoffrey Alan},
abstractNote = {Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.},
doi = {10.1016/j.jcp.2016.10.069},
journal = {Journal of Computational Physics},
number = C,
volume = 330,
place = {United States},
year = {Fri Nov 11 00:00:00 EST 2016},
month = {Fri Nov 11 00:00:00 EST 2016}
}
Web of Science
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