skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Topology Optimization: Challenges Algorithms and Applications.

Abstract

Abstract not provided.

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1429279
Report Number(s):
SAND2017-2920PE
651834
DOE Contract Number:
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the Mathematics Colloquium and the Applied Mathematics Seminar in Albuquerque, NM.
Country of Publication:
United States
Language:
English

Citation Formats

Cyr, Eric C, von Winckel, Gregory John, Gardiner, Thomas Anthony, Kouri, Drew Philip, Ridzal, Denis, Miller, Sean, and Shadid, John N. Topology Optimization: Challenges Algorithms and Applications.. United States: N. p., 2017. Web.
Cyr, Eric C, von Winckel, Gregory John, Gardiner, Thomas Anthony, Kouri, Drew Philip, Ridzal, Denis, Miller, Sean, & Shadid, John N. Topology Optimization: Challenges Algorithms and Applications.. United States.
Cyr, Eric C, von Winckel, Gregory John, Gardiner, Thomas Anthony, Kouri, Drew Philip, Ridzal, Denis, Miller, Sean, and Shadid, John N. Wed . "Topology Optimization: Challenges Algorithms and Applications.". United States. doi:. https://www.osti.gov/servlets/purl/1429279.
@article{osti_1429279,
title = {Topology Optimization: Challenges Algorithms and Applications.},
author = {Cyr, Eric C and von Winckel, Gregory John and Gardiner, Thomas Anthony and Kouri, Drew Philip and Ridzal, Denis and Miller, Sean and Shadid, John N.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Mar 01 00:00:00 EST 2017},
month = {Wed Mar 01 00:00:00 EST 2017}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • On large supercomputers, the job scheduling systems may assign a non-contiguous node allocation for user applications depending on available resources. With parallel applications using MPI (Message Passing Interface), the default process ordering does not take into account the actual physical node layout available to the application. This contributes to non-locality in terms of physical network topology and impacts communication performance of the application. In order to mitigate such performance penalties, this work describes techniques to identify suitable task mapping that takes the layout of the allocated nodes as well as the application's communication behavior into account. During the first phasemore » of this research, we instrumented and collected performance data to characterize communication behavior of critical US DOE (United States - Department of Energy) applications using an augmented version of the mpiP tool. Subsequently, we developed several reordering methods (spectral bisection, neighbor join tree etc.) to combine node layout and application communication data for optimized task placement. We developed a tool called mpiAproxy to facilitate detailed evaluation of the various reordering algorithms without requiring full application executions. This work presents a comprehensive performance evaluation (14,000 experiments) of the various task mapping techniques in lowering communication costs on Titan, the leadership class supercomputer at Oak Ridge National Laboratory.« less
  • Abstract not provided.
  • The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solutionmore » to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems.« less
  • The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solutionmore » to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems.« less