Detecting application load imbalance on high end massively parallel systems

Scientific applications should be well balanced in order to achieve high scalability on current and future high end massively parallel systems. However, the identification of sources of load imbalance in such applications is not a trivial exercise, and the current state of the art in performance analysis tools do not provide an efficient mechanism to help users to identify the main areas of load imbalance in an application. In this paper we discuss a new set of metrics that we defined to identify and measure application load imbalance. We then describe the extensions that were made to the Cray performance measurement and analysis infrastructure to detect application load imbalance and present to the user in an insightful way.