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Title: Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute

Abstract

The FASTMath SciDAC Institute addressed two key challenges that application scientists faced at the beginning of SciDAC-3. First, FASTMath helped them continue to improve the quality of their simulations by increasing accuracy and reliability of both their software and algorithms. Second, FASTMath helped them adapt their computations to make effective use of high-end computing facilities acquired by DOE over the past five years. This required the development of new mathematical algorithms that were appropriate for the physics problems being solved, implementations that scaled to million-way parallelism, and software that effectively leveraged both distributed memory and on-node parallelism. The Rensselaer Polytechnic Institute team’s efforts focused on the unstructured mesh technologies developed by FASTMath.

Authors:
 [1]
  1. Rensselaer Polytechnic Inst., Troy, NY (United States)
Publication Date:
Research Org.:
Rensselaer Polytechnic Inst., Troy, NY (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1482465
Report Number(s):
RPI-DE-SC-0006617
DOE Contract Number:  
SC0006617
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; unstructured mesh; adaptive methods

Citation Formats

Shephard, Mark. Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute. United States: N. p., 2018. Web. doi:10.2172/1482465.
Shephard, Mark. Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute. United States. doi:10.2172/1482465.
Shephard, Mark. Sat . "Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute". United States. doi:10.2172/1482465. https://www.osti.gov/servlets/purl/1482465.
@article{osti_1482465,
title = {Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute},
author = {Shephard, Mark},
abstractNote = {The FASTMath SciDAC Institute addressed two key challenges that application scientists faced at the beginning of SciDAC-3. First, FASTMath helped them continue to improve the quality of their simulations by increasing accuracy and reliability of both their software and algorithms. Second, FASTMath helped them adapt their computations to make effective use of high-end computing facilities acquired by DOE over the past five years. This required the development of new mathematical algorithms that were appropriate for the physics problems being solved, implementations that scaled to million-way parallelism, and software that effectively leveraged both distributed memory and on-node parallelism. The Rensselaer Polytechnic Institute team’s efforts focused on the unstructured mesh technologies developed by FASTMath.},
doi = {10.2172/1482465},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {11}
}