Software Analysis Techniques to Approximate Data Centric Direct Measurements

Data centric analysis using direct measurements has been established as a successful performance analysis technique. The information gathered with this technique can be used to address data locality problems and other issues. Existing approaches rely on special hardware support which is needed to negate a ‘skid’ factor. Our approach is viable on hardware where the skid factor is an issue. Prior methods also rely on maintaining runtime information about memory allocation addresses for variables, which may lead to program perturbation. Our approach uses software analysis to eliminate the need for maintaining allocation and free records. We show that by using heuristics our technique can attribute data centric values to program variables and maintain the approximate rank-order found by using traditional techniques.