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Title: Climate Modeling using High-Performance Computing

Abstract

The Center for Applied Scientific Computing (CASC) and the LLNL Climate and Carbon Science Group of Energy and Environment (E&E) are working together to improve predictions of future climate by applying the best available computational methods and computer resources to this problem. Over the last decade, researchers at the Lawrence Livermore National Laboratory (LLNL) have developed a number of climate models that provide state-of-the-art simulations on a wide variety of massively parallel computers. We are now developing and applying a second generation of high-performance climate models.

Authors:
;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
928554
Report Number(s):
UCRL-TR-220786
TRN: US200812%%513
DOE Contract Number:
W-7405-ENG-48
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; 54 ENVIRONMENTAL SCIENCES; CARBON; CLIMATE MODELS; CLIMATES; COMPUTERS; LAWRENCE LIVERMORE NATIONAL LABORATORY; SIMULATION

Citation Formats

Mirin, A A, and Wickett, M. Climate Modeling using High-Performance Computing. United States: N. p., 2006. Web. doi:10.2172/928554.
Mirin, A A, & Wickett, M. Climate Modeling using High-Performance Computing. United States. doi:10.2172/928554.
Mirin, A A, and Wickett, M. Thu . "Climate Modeling using High-Performance Computing". United States. doi:10.2172/928554. https://www.osti.gov/servlets/purl/928554.
@article{osti_928554,
title = {Climate Modeling using High-Performance Computing},
author = {Mirin, A A and Wickett, M},
abstractNote = {The Center for Applied Scientific Computing (CASC) and the LLNL Climate and Carbon Science Group of Energy and Environment (E&E) are working together to improve predictions of future climate by applying the best available computational methods and computer resources to this problem. Over the last decade, researchers at the Lawrence Livermore National Laboratory (LLNL) have developed a number of climate models that provide state-of-the-art simulations on a wide variety of massively parallel computers. We are now developing and applying a second generation of high-performance climate models.},
doi = {10.2172/928554},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Apr 20 00:00:00 EDT 2006},
month = {Thu Apr 20 00:00:00 EDT 2006}
}

Technical Report:

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  • The Center for Applied Scientific Computing (CASC) and the LLNL Climate and Carbon Science Group of Energy and Environment (E and E) are working together to improve predictions of future climate by applying the best available computational methods and computer resources to this problem. Over the last decade, researchers at the Lawrence Livermore National Laboratory (LLNL) have developed a number of climate models that provide state-of-the-art simulations on a wide variety of massively parallel computers. We are now developing and applying a second generation of high-performance climate models. Through the addition of relevant physical processes, we are developing an earthmore » systems modeling capability as well.« less
  • The Center for Applied Scientific Computing (CASC) and the LLNL Atmospheric Science Division (ASD) are working together to improve predictions of future climate by applying the best available computational methods and computer resources to this problem. Over the last decade, researchers at the Lawrence Livermore National Laboratory (LLNL) have developed a number of climate models that provide state-of-the-art simulations on a wide variety of massively parallel computers. We are now developing and applying a second generation of high-performance climate models. As part of LLNL's participation in DOE's Scientific Discovery through Advanced Computing (SciDAC) program, members of CASC and ASD aremore » collaborating with other DOE labs and NCAR in the development of a comprehensive, next-generation global climate model. This model incorporates the most current physics and numerics and capably exploits the latest massively parallel computers. One of LLNL's roles in this collaboration is the scalable parallelization of NASA's finite-volume atmospheric dynamical core. We have implemented multiple two-dimensional domain decompositions, where the different decompositions are connected by high-speed transposes. Additional performance is obtained through shared memory parallelization constructs and one-sided interprocess communication. The finite-volume dynamical core is particularly important to atmospheric chemistry simulations, where LLNL has a leading role.« less
  • This work has explored the preliminary design of a Computational Fluid Dynamics (CFD) tool for the analysis of transient vehicle underhood thermo-hydrodynamic events using high performance computing platforms. The goal of this tool will be to extend the capabilities of an existing established CFD code, STAR-CD, allowing the car manufacturers to analyze the impact of transient operational events on the underhood thermal management by exploiting the computational efficiency of modern high performance computing systems. In particular, the project has focused on the CFD modeling of the radiator behavior during a specified transient. The 3-D radiator calculations were performed using STAR-CD,more » which can perform both steady-state and transient calculations, on the cluster computer available at ANL in the Nuclear Engineering Division. Specified transient boundary conditions, based on experimental data provided by Adapco and DaimlerChrysler were used. The possibility of using STAR-CD in a transient mode for the entire period of time analyzed has been compared with other strategies which involve the use of STAR-CD in a steady-state mode at specified time intervals, while transient heat transfer calculations would be performed for the rest of the time. The results of these calculations have been compared with the experimental data provided by Adapco/DaimlerChrysler and recommendations for future development of an optimal strategy for the CFD modeling of transient thermo-hydrodynamic events have been made. The results of this work open the way for the development of a CFD tool for the transient analysis of underhood thermo-hydrodynamic events, which will allow the integrated transient thermal analysis of the entire cooling system, including both the engine block and the radiator, on high performance computing systems.« less
  • The electric utility industry is undergoing significant transformations in its operation model, including a greater emphasis on automation, monitoring technologies, and distributed energy resource management systems (DERMS). With these changes and new technologies, while driving greater efficiencies and reliability, these new models may introduce new vectors of cyber attack. The appropriate cybersecurity controls to address and mitigate these newly introduced attack vectors and potential vulnerabilities are still widely unknown and performance of the control is difficult to vet. This proposal argues that modeling and simulation (M&S) is a necessary tool to address and better understand these problems introduced by emergingmore » technologies for the grid. M&S will provide electric utilities a platform to model its transmission and distribution systems and run various simulations against the model to better understand the operational impact and performance of cybersecurity controls.« less
  • We present a case study of performance measurement and modeling of a CCA (Common Component Architecture) component-based application in a high performance computing environment. We explore issues peculiar to component-based HPC applications and propose a performance measurement infrastructure for HPC based loosely on recent work done for Grid environments. A prototypical implementation of the infrastructure is used to collect data for a three components in a scientific application and construct performance models for two of them. Both computational and message-passing performance are addressed.