CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications

Praveen Elakkumanan; Lushan Liu; Vijay Kumar Vankadara; Ramalingam Sridhar

doi:10.1109/MWSCAS.2005.1594493

CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications

Praveen Elakkumanan
, Lushan Liu
, Vijay Kumar Vankadara
, Ramalingam Sridhar

Department of Computer Science and Engineering

SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

In this paper, we present a Cache HIerarchy Design using DAta Mining (CHIDDAM) methodology to improve the memory efficiency for a given type of commercial application and its data set characteristics. Performance analysis, workload characterization, decision tree induction (a classification data mining method), and a greedy search algorithm are used in determining the optimal number of levels and sizes of the cache in the hierarchy. SimICS, a full system simulator, is used to simulate an x86 machine loaded with Enterprise Linux Operating System. Popular representative applications in data mining, such as, C4.5 and Apriori are used as benchmark applications for our simulation analysis. However, the proposed methodology is generic and can be applied to other applications for determine the design details of memory subsystems.

Original language	English
Title of host publication	2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005
Pages	1888-1891
Number of pages	4
DOIs	https://doi.org/10.1109/MWSCAS.2005.1594493
State	Published - 2005
Event	2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005 - Cincinnati, OH, United States Duration: Aug 7 2005 → Aug 10 2005

Publication series

Name	Midwest Symposium on Circuits and Systems
Volume	2005
ISSN (Print)	1548-3746

Conference

Conference	2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005
Country/Territory	United States
City	Cincinnati, OH
Period	08/7/05 → 08/10/05

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10.1109/MWSCAS.2005.1594493

Cite this

Elakkumanan, P., Liu, L., Vankadara, V. K., & Sridhar, R. (2005). CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications. In 2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005 (pp. 1888-1891). Article 1594493 (Midwest Symposium on Circuits and Systems; Vol. 2005). https://doi.org/10.1109/MWSCAS.2005.1594493

@inproceedings{17c62efa744848dc8ceec703c28d5ae0,

title = "CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications",

abstract = "In this paper, we present a Cache HIerarchy Design using DAta Mining (CHIDDAM) methodology to improve the memory efficiency for a given type of commercial application and its data set characteristics. Performance analysis, workload characterization, decision tree induction (a classification data mining method), and a greedy search algorithm are used in determining the optimal number of levels and sizes of the cache in the hierarchy. SimICS, a full system simulator, is used to simulate an x86 machine loaded with Enterprise Linux Operating System. Popular representative applications in data mining, such as, C4.5 and Apriori are used as benchmark applications for our simulation analysis. However, the proposed methodology is generic and can be applied to other applications for determine the design details of memory subsystems.",

author = "Praveen Elakkumanan and Lushan Liu and Vankadara, \{Vijay Kumar\} and Ramalingam Sridhar",

year = "2005",

doi = "10.1109/MWSCAS.2005.1594493",

language = "English",

isbn = "0780391977",

series = "Midwest Symposium on Circuits and Systems",

pages = "1888--1891",

booktitle = "2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005",

note = "2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005 ; Conference date: 07-08-2005 Through 10-08-2005",

}

Elakkumanan, P, Liu, L, Vankadara, VK & Sridhar, R 2005, CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications. in 2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005., 1594493, Midwest Symposium on Circuits and Systems, vol. 2005, pp. 1888-1891, 2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005, Cincinnati, OH, United States, 08/7/05. https://doi.org/10.1109/MWSCAS.2005.1594493

CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications. / Elakkumanan, Praveen; Liu, Lushan; Vankadara, Vijay Kumar et al.
2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005. 2005. p. 1888-1891 1594493 (Midwest Symposium on Circuits and Systems; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this paper, we present a Cache HIerarchy Design using DAta Mining (CHIDDAM) methodology to improve the memory efficiency for a given type of commercial application and its data set characteristics. Performance analysis, workload characterization, decision tree induction (a classification data mining method), and a greedy search algorithm are used in determining the optimal number of levels and sizes of the cache in the hierarchy. SimICS, a full system simulator, is used to simulate an x86 machine loaded with Enterprise Linux Operating System. Popular representative applications in data mining, such as, C4.5 and Apriori are used as benchmark applications for our simulation analysis. However, the proposed methodology is generic and can be applied to other applications for determine the design details of memory subsystems.

AB - In this paper, we present a Cache HIerarchy Design using DAta Mining (CHIDDAM) methodology to improve the memory efficiency for a given type of commercial application and its data set characteristics. Performance analysis, workload characterization, decision tree induction (a classification data mining method), and a greedy search algorithm are used in determining the optimal number of levels and sizes of the cache in the hierarchy. SimICS, a full system simulator, is used to simulate an x86 machine loaded with Enterprise Linux Operating System. Popular representative applications in data mining, such as, C4.5 and Apriori are used as benchmark applications for our simulation analysis. However, the proposed methodology is generic and can be applied to other applications for determine the design details of memory subsystems.

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M3 - Conference contribution

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BT - 2005 IEEE International 48th Midwest Symposium on Circuits and Systems, MWSCAS 2005

Y2 - 7 August 2005 through 10 August 2005

ER -

CHIDDAM: A data mining based technique for cache hierarchy determination in commercial applications

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