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Title: PIPER: Performance Insights for Programmers and Exascale Runtimes

Abstract

During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computingmore » or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.« less

Authors:
 [1]
  1. Univ. of Utah, Salt Lake City, UT (United States)
Publication Date:
Research Org.:
Univ. of Utah, Salt Lake City, UT (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
Contributing Org.:
LLNL
OSTI Identifier:
1481005
Report Number(s):
DOE-Utah-10498
DOE Contract Number:  
SC0010498
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; data analysis; visualization; topological analysis; data management; statistical methods; machine learning

Citation Formats

Pascucci, Valerio. PIPER: Performance Insights for Programmers and Exascale Runtimes. United States: N. p., 2018. Web. doi:10.2172/1481005.
Pascucci, Valerio. PIPER: Performance Insights for Programmers and Exascale Runtimes. United States. doi:10.2172/1481005.
Pascucci, Valerio. Tue . "PIPER: Performance Insights for Programmers and Exascale Runtimes". United States. doi:10.2172/1481005. https://www.osti.gov/servlets/purl/1481005.
@article{osti_1481005,
title = {PIPER: Performance Insights for Programmers and Exascale Runtimes},
author = {Pascucci, Valerio},
abstractNote = {During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.},
doi = {10.2172/1481005},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {11}
}