Estimating computational requirements in multi-threaded applications

Juan F. Pérez, Giuliano Casale, Sergio Pacheco-Sanchez

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Performance models provide effective support for managing quality-of-service (QoS) and costs of enterprise applications. However, expensive high-resolution monitoring would be needed to obtain key model parameters, such as the CPU consumption of individual requests, which are thus more commonly estimated from other measures. However, current estimators are often inaccurate in accounting for scheduling in multi-threaded application servers. To cope with this problem, we propose novel linear regression and maximum likelihood estimators. Our algorithms take as inputs response time and resource queue measurements and return estimates of CPU consumption for individual request types. Results on simulated and real application datasets indicate that our algorithms provide accurate estimates and can scale effectively with the threading levels.

Translated title of the contributionEstimación de los requisitos computacionales en aplicaciones multiproceso
Original languageEnglish (US)
Article number6926798
Pages (from-to)264-278
Number of pages15
JournalIEEE Transactions on Software Engineering
Volume41
Issue number3
DOIs
StatePublished - Mar 1 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software

Fingerprint Dive into the research topics of 'Estimating computational requirements in multi-threaded applications'. Together they form a unique fingerprint.

Cite this