Phase Tracking and Prediction

Timothy Sherwood, Suleyman Sair, and Brad Calder

30th International Symposium on Computer Architecture, June 2003.


In a single second a modern processor can execute billions of instructions. Obtaining a bird's eye view of the behavior of a program at these speeds can be a difficult task when all that is available is cycle by cycle examination. In many programs, behavior is anything but steady state, and understanding the patterns of behavior, at run-time, can unlock a multitude of optimization opportunities.

In this paper, we present a unified profiling architecture that can efficiently capture, classify, and predict phase-based program behavior on the largest of time scales. By examining the proportion of instructions that were executed from different sections of code, we can find generic phases that correspond to changes in behavior across many metrics. By classifying phases generically, we avoid the need to identify phases for each optimization, and enable a unified prediction scheme that can forecast future behavior. Our analysis shows that our design can capture phases that account for over 80% of execution using less that 500 bytes of on-chip memory.