As useful as performance counters are, the meaning of reported aggregate event counts is sometimes questionable. Questions arise due to unanticipated processor behavior, overhead associated with the interface, the granularity of the monitored code, hardware errors, and lack of standards w.r.t. event definitions. To explore these issues, we are conducting a sequence of studies using carefully-crafted microbenchmarks that permit the accurate prediction of event counts and investigation of the differences between hardware-reported and predicted event counts. This paper presents the methodology employed, some of the microbenchmarks developed, and some of the information uncovered to date. The information provided by this work allows application developers to better understand the data provided by hardware performance counters and better utilize it to tune application performance. A goal of this research is to develop a cross-platform microbenchmark suite that can be used by application developers for these purposes. Some of the microbenchmarks in this suite are discussed in the paper.
['Roberto Araiza', 'Maria Gabriela Aguilera', 'Thientam Pham', 'Patricia J. Teller']
Towards a cross-platform microbenchmark suite for evaluating hardware performance counter data