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Title: Memory Scalability and Efficiency Analysis of Parallel Codes

Abstract

Memory scalability is an enduring problem and bottleneck that plagues many parallel codes. Parallel codes designed for High Performance Systems are typically designed over the span of several, and in some instances 10+, years. As a result, optimization practices which were appropriate for earlier systems may no longer be valid and thus require careful optimization consideration. Specifically, parallel codes whose memory footprint is a function of their scalability must be carefully considered for future exa-scale systems. In this paper we present a methodology and tool to study the memory scalability of parallel codes. Using our methodology we evaluate an application s memory footprint as a function of scalability, which we coined memory efficiency, and describe our results. In particular, using our in-house tools we can pinpoint the specific application components which contribute to the application s overall memory foot-print (application data- structures, libraries, etc.).

Authors:
 [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1265552
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Cray User Group, Chicago, IL, USA, 20150426, 20150430
Country of Publication:
United States
Language:
English

Citation Formats

Janjusic, Tommy, and Kartsaklis, Christos. Memory Scalability and Efficiency Analysis of Parallel Codes. United States: N. p., 2015. Web.
Janjusic, Tommy, & Kartsaklis, Christos. Memory Scalability and Efficiency Analysis of Parallel Codes. United States.
Janjusic, Tommy, and Kartsaklis, Christos. Thu . "Memory Scalability and Efficiency Analysis of Parallel Codes". United States. doi:.
@article{osti_1265552,
title = {Memory Scalability and Efficiency Analysis of Parallel Codes},
author = {Janjusic, Tommy and Kartsaklis, Christos},
abstractNote = {Memory scalability is an enduring problem and bottleneck that plagues many parallel codes. Parallel codes designed for High Performance Systems are typically designed over the span of several, and in some instances 10+, years. As a result, optimization practices which were appropriate for earlier systems may no longer be valid and thus require careful optimization consideration. Specifically, parallel codes whose memory footprint is a function of their scalability must be carefully considered for future exa-scale systems. In this paper we present a methodology and tool to study the memory scalability of parallel codes. Using our methodology we evaluate an application s memory footprint as a function of scalability, which we coined memory efficiency, and describe our results. In particular, using our in-house tools we can pinpoint the specific application components which contribute to the application s overall memory foot-print (application data- structures, libraries, etc.).},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Conference:
Other availability
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