Abstract—In this work, we leverage hardware performance

counters-collected data to automatically group program fail-

ures that stem from closely related causes into clusters, which

can in turn help developers prioritize failures as well as

diagnose their causes. Hardware counters have been used

for performance analysis of software systems in the past. By

contrast, in this paper they are used as abstraction mechanisms

for program executions. The results of our feasibility studies

conducted on two widely-used applications suggest that hard-

ware counters-collected data can be used to reliably classify

failures.