Diierential Prooling

Performance can be a critical aspect of software quality ; in some systems, poor performance can cause-nancial loss, physical damage, or even death. In such cases, it is imperative to identify system performance problems before deployment, preferably well before implementation. Unfortunately, the size of most software systems grossly exceeds the capacity of current performance-modelling techniques. Hence, there is a need for techniques to quickly identify the portions of the system that are performance-critical. These portions are often small enough to be modelled directly. This paper describes one such technique. This technique combines prooles taken at diierent loads to help locate performance bottlenecks, even those that are distributed widely throughout a large program or system , such as those concealed within macros or inlined functions. This paper also describes how this technique may be used to pinpoint certain types of performance bottlenecks in large programs running on large-scale shared-memory multiprocessors. In this environment, the critical bottleneck might consume only a small fraction of the total CPU time, since typical critical sections can consume at most one CPU's worth of computation. This sort of bottleneck, particularly when widely distributed throughout the program under consideration , is often invisible to traditional prooling techniques .