BibSonomy publications for /author/EnoWed Feb 08 00:00:00 CET 2012ITCconf/itc/1994388-394The PowerPC 603TM Microprocessor: An Array Built-In Self-Test Mechanism.1994dblp Thu Dec 01 00:00:00 CET 2011IJICST21-13Who Blogs in 2010?: An Updated Look at Individual Differences in Blogging.12011dblp Tue Nov 15 00:00:00 CET 2011Video Processing and Computational Videoconf/dagstuhl/2010video104-123Lecture Notes in Computer ScienceSilhouette-Based Variational Methods for Single View Reconstruction.70822010dblp Wed Nov 02 00:00:00 CET 2011IEEE Internet Computing378-82Generating Synthetic Data to Match Data Mining Patterns.122008dblp Fri Oct 21 00:00:00 CEST 2011IEEE Internet Computing546-52Virtual and Real-World Ontology Services.152011dblp Wed Aug 10 00:00:00 CEST 2011EMMCVPRconf/emmcvpr/2011177-190Lecture Notes in Computer ScienceSpace-Varying Color Distributions for Interactive Multiregion Segmentation: Discrete versus Continuous Approaches.68192011dblp Tue Jul 05 00:00:00 CEST 2011UMAPconf/um/201187-98Lecture Notes in Computer ScienceHybrid User Preference Models for Second Life and OpenSimulator Virtual Worlds.67872011dblp Tue Jul 05 00:00:00 CEST 2011LADCconf/ladc/20032-3Lecture Notes in Computer ScienceSafety-Critical Systems in Air Traffic Management.28472003dblp Fri Jul 01 00:00:00 CEST 2011INFOCOMconf/infocom/20111098-1106Dynamic right-sizing for power-proportional data centers.2011dblp Mon Apr 18 00:00:00 CEST 2011EuroSysconf/eurosys/2011169-182Sierra: practical power-proportionality for data center storage.2011dblp Wed Mar 09 00:00:00 CET 2011ACCV (1)conf/accv/2010-153-64Lecture Notes in Computer ScienceImage-Based 3D Modeling via Cheeger Sets.64922010dblp Sat Feb 19 00:00:00 CET 2011Computers in Human Behavior51993-2004Who blogs? Personality predictors of blogging.242008dblp Fri Dec 03 00:00:00 CET 2010SIGMETRICS Performance Evaluation Review426-33Towards versatile performance models for complex, popular applications.372010dblp Tue Nov 23 00:00:00 CET 2010CompSysTechconf/compsystech/200987Python prevails.2009dblp Tue Sep 28 11:48:20 CEST 2010 SIGMETRICS 2010, Proceedings of the 2010 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, New York, New York, USA, 14-18 June2010 conf/sigmetrics/20101--12Practical performance models for complex, popular applications2010Perhaps surprisingly, no practical performance models exist for popular (and complex) client applications such as Adobe's Creative Suite, Microsoft's Office and Visual Studio, Mozilla, Halo 3, etc. There is currently no tool that automatically answers program developers', IT administrators' and end-users' simple what-if questions like "what happens to the performance of my favorite application X if I upgrade from Windows Vista to Windows 7?". This paper describes our approach towards constructing practical, versatile performance models to address this problem. The goal is to have these models be useful for application developers to help expand application testing coverage and for IT administrators to assist with understanding the performance consequences of a software, hardware or configuration change. This paper's main contributions are in system building and performance modeling. We believe we have built applications that are easier to model because we have proactively instrumented them to export their state and associated metrics. This application-specific monitoring is always on and interesting data is collected from real, "in-the-wild" deployments. The models we are experimenting with are based on statistical techniques. They require no modifications to the OS or applications beyond the above instrumentation, and no explicit a priori model on how an OS or application should behave. We are in the process of learning from models we have constructed for several Microsoft products, including the Office suite, Visual Studio and Media Player. This paper presents preliminary findings from a large user deployment (several hundred thousand user sessions) of these applications that show the coverage and limitations of such models. These findings pushed us to move beyond averages/means and go into some depth into why client application performance has an inherently large variance.Mon Sep 27 00:00:00 CEST 2010SIGMETRICS/Performanceconf/sigmetrics/20063-14Stardust: tracking activity in a distributed storage system.2006dblp Mon Sep 20 00:00:00 CEST 2010FASTconf/fast/200761-76Argon: Performance Insulation for Shared Storage Servers.2007dblp Wed Sep 15 00:00:00 CEST 2010GPC Workshopsconf/gpc/2008w49-56Towards a Domain-Specific Modeling Language for Customer Data Integration Workflow.2008dblp Mon Aug 09 00:00:00 CEST 2010Web3Dconf/vrml/2010157-164Linking behavior in a virtual world environment.2010dblp Wed Jul 21 16:07:27 CEST 2010LRECconf/lrec/2010Medefaidrin: Resources Documenting the Birth and Death Language Life-cycle.2010dblp