Automatic Platform-Independent Monitoring and Ranking of Hardware Resource Utilization

In this paper, we discuss a method for automatic monitoring of hardware and software events using performance monitoring counters. Computer applications are complex and utilize a broad spectra of the available hardware resources, where multiple performance counters can be of significant interest to understand. The number of performance counters that can be captured simultaneously is, however, small due to hardware limitations in most modern computers. We suggest a platform independent solution to automatically retrieve hardware events from an underlying architecture. Moreover, to mitigate the hardware limitations we propose a mechanism that pinpoints the most relevant performance counters for an application's performance. In our proposal, we utilize the Pearson's correlation coefficient to rank the most relevant performance counters and filter out those that are most relevant and ignore the rest.