research-article

Performance Analysis of Applications in the Context of Architectural Rooflines

Authors:

Allen MalonyAuthors Info & Claims

ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

Pages 345 - 348

https://doi.org/10.1145/3030207.3030232

Published: 17 April 2017 Publication History

Abstract

Intuitive visual representations of architecture capabilities and the performance of applications are critical to enabling effective performance analysis, which in turn guides optimizations. The Roofline Model and its derivatives provide such an intuitive representation of the best achievable performance on a given architecture. The Roofline Toolkit project is a collaboration among researchers at Argonne National Laboratory, Lawrence Berkeley National Laboratory, and the University of Oregon and consists of three principal components: hardware characterization, software characterization, and data manipulation, which includes a visualization interface. These components address the different aspects of performance data acquisition and manipulation required for performance analysis, modeling and optimization of applications. In this paper we introduce an implementation of the third component, a system for visualizing roofline charts and managing roofline performance analysis data. We demonstrate analysis of an application use case within this framework and outline future directions for this type of performance analysis and visualization.

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Cited By

Calotoiu AGraf AHoefler TLorenz DRinke SWolf F(2018)Lightweight Requirements Engineering for Exascale Co-design2018 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER.2018.00038(201-211)Online publication date: Sep-2018
https://doi.org/10.1109/CLUSTER.2018.00038

Index Terms

Performance Analysis of Applications in the Context of Architectural Rooflines
1. Human-centered computing
  1. Visualization
2. Software and its engineering
  1. Software organization and properties
    1. Extra-functional properties
      1. Software performance

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

April 2017

450 pages

ISBN:9781450344043

DOI:10.1145/3030207

General Chairs:
Walter Binder
Università della Svizzera Italiana, Switzerland
,
Vittorio Cortellessa
Università dell'Aquila, Italy
,
Program Chairs:
Anne Koziolek
Karlsruhe Institute of Technology, Germany
,
Evgenia Smirni
College of William & Mary, USA
,
Meikel Poess
Oracle Corporation, USA

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGSOFT: ACM Special Interest Group on Software Engineering
SPEC: SPEC Research Group

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2017

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Department of Energy Office of Advanced Scientific Computing Research

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ICPE '17

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ICPE '17: ACM/SPEC International Conference on Performance Engineering

April 22 - 26, 2017

L'Aquila, Italy

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ICPE '17 Paper Acceptance Rate 27 of 83 submissions, 33%;

Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

Calotoiu AGraf AHoefler TLorenz DRinke SWolf F(2018)Lightweight Requirements Engineering for Exascale Co-design2018 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER.2018.00038(201-211)Online publication date: Sep-2018
https://doi.org/10.1109/CLUSTER.2018.00038

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