Why you should care about quantile regression
Augusto Born De Oliveira, Sebastian Fischmeister, et al.
ASPLOS 2013
The performance of a program often varies significantly over the course of the program's run. Thus, to understand the performance of a program it is valuable to look not just at end-to-end metrics (e.g. total number of cache misses) but also the time-varying performance of the program. Unfortunately, analyzing time-varying performance is both cumbersome and difficult. This paper makes three contributions, all geared toward helping others in working with traces. First, it describes a system, the TraceAnalyzer, designed specifically for working with performance traces; a performance trace captures the time-varying performance of a program run. Second, it describes lessons that we have learned from many years of working with these traces. Finally, it uses a case study to demonstrate how we have used the TraceAnalyzer to understand a performance anomaly. © 2010 John Wiley & Sons, Ltd.
Augusto Born De Oliveira, Sebastian Fischmeister, et al.
ASPLOS 2013
Matthias Hauswirth, Peter F. Sweeney, et al.
ACM SIGPLAN Notices
Todd Mytkowicz, Amer Diwan, et al.
ASPLOS 2009
Matthias Hauswirth, Amer Diwan, et al.
OOPSLA 2004