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Title: FleCSI. Developing Flexible Computational Science Infrastructure for Multi-Physics Application Development

Abstract

This report is a presentation for an operational meeting concerning physics computation.

Authors:
 [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1237413
Report Number(s):
LA-UR-16-20690
DOE Contract Number:
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Computer Science

Citation Formats

Bergen, Benjamin Karl. FleCSI. Developing Flexible Computational Science Infrastructure for Multi-Physics Application Development. United States: N. p., 2016. Web. doi:10.2172/1237413.
Bergen, Benjamin Karl. FleCSI. Developing Flexible Computational Science Infrastructure for Multi-Physics Application Development. United States. doi:10.2172/1237413.
Bergen, Benjamin Karl. 2016. "FleCSI. Developing Flexible Computational Science Infrastructure for Multi-Physics Application Development". United States. doi:10.2172/1237413. https://www.osti.gov/servlets/purl/1237413.
@article{osti_1237413,
title = {FleCSI. Developing Flexible Computational Science Infrastructure for Multi-Physics Application Development},
author = {Bergen, Benjamin Karl},
abstractNote = {This report is a presentation for an operational meeting concerning physics computation.},
doi = {10.2172/1237413},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 2
}

Technical Report:

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  • This is a final report of the DOE award DE-SC0001132, Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation. This document describes the achievements of the goals, and resulting research made possible by this award.
  • No abstract provided.
  • FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer providesmore » the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.« less
  • A variety of computer programs is used to fulfill the different requirements, generated by the various research programs, for satellite orbit data. Revisions to these programs are presented which enlarge the input/output capabilities, improve the accuracy of calculations, or extend the range of problems that can be addressed. Results are presented of investigations of the comparative accuracy of available programs for satellite orbit prediction and solar ephemeris calculation. Occasionally large-scale computer codes useful for geophysical analyses, but developed elsewhere, must be adapted to the needs of AFGL research programs and modified for use on the 6600 system. Cases in pointmore » are a code for predicting the proton and electron environments in the magnetosphere and another for transforming between geomagnetic and geographical coordinate systems. Modifications to these programs and procedures for their operational usage are presented. Atmospheric density modeling plays an important role in satellite orbit determination. Results are presented for efforts to incoporate new density models into orbit determination programs, evaluate the performance of different density models in orbit determination applications, and provide methods for model development by applying multiple regression to experimental data.« less