Towards an Objective Metric for the Performance of Exact Triangle Count

Mark P. Blanco, Scott McMillan, Tze Meng Low
{"title":"Towards an Objective Metric for the Performance of Exact Triangle Count","authors":"Mark P. Blanco, Scott McMillan, Tze Meng Low","doi":"10.1109/HPEC43674.2020.9286188","DOIUrl":null,"url":null,"abstract":"The performance of graph algorithms is often measured in terms of the number of traversed edges per second (TEPS). However, this performance metric is inadequate for a graph operation such as exact triangle counting. In triangle counting, execution times on graphs with a similar number of edges can be distinctly different as demonstrated by results from the past Graph Challenge entries. We discuss the need for an objective performance metric for graph operations and the desired characteristics of such a metric such that it more accurately captures the interactions between the amount of work performed and the capabilities of the hardware on which the code is executed. Using exact triangle counting as an example, we derive a metric that captures how certain techniques employed in many implementations improve performance. We demonstrate that our proposed metric can be used to evaluate and compare multiple approaches for triangle counting, using a SIMD approach as a case study against a scalar baseline.","PeriodicalId":168544,"journal":{"name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC43674.2020.9286188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The performance of graph algorithms is often measured in terms of the number of traversed edges per second (TEPS). However, this performance metric is inadequate for a graph operation such as exact triangle counting. In triangle counting, execution times on graphs with a similar number of edges can be distinctly different as demonstrated by results from the past Graph Challenge entries. We discuss the need for an objective performance metric for graph operations and the desired characteristics of such a metric such that it more accurately captures the interactions between the amount of work performed and the capabilities of the hardware on which the code is executed. Using exact triangle counting as an example, we derive a metric that captures how certain techniques employed in many implementations improve performance. We demonstrate that our proposed metric can be used to evaluate and compare multiple approaches for triangle counting, using a SIMD approach as a case study against a scalar baseline.
探讨精确三角计数性能的客观度量
图算法的性能通常以每秒遍历的边数(TEPS)来衡量。然而,这种性能度量对于像精确三角形计数这样的图形操作来说是不够的。在三角形计数中,具有相似边数的图的执行时间可以明显不同,这可以从过去Graph Challenge条目的结果中得到证明。我们讨论了对图形操作的客观性能度量的需求,以及这种度量所需的特征,以便更准确地捕获所执行的工作量与执行代码的硬件功能之间的交互。以精确三角形计数为例,我们推导了一个度量,该度量捕获了在许多实现中使用的某些技术如何提高性能。我们演示了我们提出的度量可以用来评估和比较三角形计数的多种方法,使用SIMD方法作为针对标量基线的案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信