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공공누리This item is licensed Korea Open Government License

Title
Interference-aware Co-scheduling Method based on Classification of Application Characteristics from Hardware Performance Counter using Data Mining
Author(s)
최지은남덕윤박근철
Publisher
Baltzer Science Publishers
Publication Year
2019-06-12
Abstract
Computational scientists and engineers who are eager to obtain the best performance of scientific applications need efficient application characterization methods to successfully exploit high-performance hardware resources. However, modern processors are accompanied by high-bandwidth on-chip memory or a large number of cores. Therefore, application characterization research that takes into account the newly introduced hardware features in next-generation high performance computing environments is insufficient and complex. In this paper, we propose a simple and fast method to classify the application characteristics in systems state-of-the-art processors using hardware performance counters. The proposed method utilizes hardware performance counters to monitor hardware events related to system performance. A clustering approach is adopted that requires limited understanding of the correlation between hardware events and application characteristics. The application characterization technique is applied to NAS parallel benchmarks in two systems, including Intel Knights Landing and SkyLake Xeon processors. We demonstrate that the proposed techniques can capture system and application characteristics and provide users with useful insights into application execution.
Keyword
Application Characteristics Classification; Performance Counter Event; Data Mining; Hardware Performance Counter; Resource Interference; Interference-aware Co-scheduling
Journal Title
Cluster computing : the Journal of networks, software tools and applications;
ISSN
1386-7857
DOI
10.1007/s10586-019-02949-7
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Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/16246
Fulltext
 https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=NART100983028
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