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Characterization, monitoring and evaluation of operational performance trends on server processor hardware

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Sithole, Ernest, McClean, Sally, Bryan, Scotney, Parr, Gerard, Adrian, Moore, Bustard, David and Dawson, Stephen (2011) Characterization, monitoring and evaluation of operational performance trends on server processor hardware. In: ICPE '11 the second joint WOSP/SIPEW international conference on Performance engineering , Karlsruhe, Germany. The Association for Computing Machinery. 12 pp. [Conference contribution]

Full text not available from this repository.

DOI: 10.1145/1958746.1958801

Abstract

Enterprise IT environments have seen a sharp growth in content use due to the popularity of on-demand data-intensive applications. In turn, the huge demand in content has spawned off major developments such as growth and distribution of computing nodes as well as the adoption of various implementation technologies. Given the complexity brought to the makeup of business computing environments in addressing the above-mentioned factors, the critical planning task of determining the appropriate infrastructure sizes for supporting firm Quality of Service (QoS) guarantees becomes a very challenging undertaking to fulfil. Benchmarking methods are widely employed in calibrating attainable performance in IT solutions, but these have the drawback of presenting output performance metrics as composite measurements that only give an end-to-end perspective. As an enhancement to benchmarking approaches, we explore the use of Performance Monitoring Counters (PMCs) in obtaining detailed operational performance of CPU and memory hardware. Performance Monitoring Counters (PMCs) are onchip registers found on most modern processor hardware. We use PMC-derived measurements to validate cache performance trends that have been derived analytically, and in the course of validations, PMC data is also used to investigate the nature and character of surges in cache miss events, which emerge as the memory load generated by runtime processes increases.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:19062
Deposited By:Professor Sally McClean
Deposited On:15 Jul 2011 11:00
Last Modified:15 Jul 2011 11:00

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