A Modeling Approach to Hardware Analysis of the Heterogeneous DEAC Cluster

被引：0

作者：

Freedman, Riana J. ^{[1
]}

Valles, Damian ^{[2
]}

机构：

[1] Wake Forest Univ, Dept Comp Sci, Winston Salem, NC USA

[2] Wake Forest Univ, Informat Syst Dept, Winston Salem, NC USA

来源：

2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & COMPUTATIONAL INTELLIGENCE (CSCI) | 2016年

关键词：

cluster; benchmark; performance; modeling;

D O I：

10.1109/CSCI.2016.271

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The employment of five distinct benchmarks on the Distributed Environment for Academic Computing (DEAC) Cluster at Wake Forest University provides meaningful metrics of cluster processor and memory performance. Given the heterogeneous nature of the DEAC Cluster, the benchmarks taken consider the specific processor architectures comprising the cluster. The data obtained will be assessed via two modeling approaches: (1) linear and polynomial regression and (2) Bayes' Theorem. The most suitable modeling approach for characterizing the DEAC Cluster is sought through the assessment of these models.

引用

页码：1408 / 1409

页数：2

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