PAPI 5: Measuring power, energy, and the cloud

The PAPI library [1] was originally developed to provide portable access to the hardware performance counters found on a diverse collection of modern microprocessors. Rather than learning and writing to a new performance infrastructure each time code is moved to a new machine, measurement code can be written to the PAPI API which abstracts away the underlying interface. Over time, other system components besides the processor have gained performance interfaces (for example, GPUs and network interfaces). PAPI was redesigned to have a component architecture to allow modular access to these new sources of performance data [2]. In addition to incremental changes in processor support, the recent PAPI 5 release adds support for two emerging concerns in the high-performance landscape: energy consumption and cloud computing. As processor densities climb, the thermal properties and energy usage of high performance systems are becoming increasingly important. We have extended the PAPI interface to simultaneously monitor processor metrics, thermal sensors, and power meters to provide clues for correlating algorithmic activity with thermal response and energy consumption. We have also extended PAPI to provide support for running inside of Virtual Machines (VMs). This ongoing work will enable developers to use PAPI to engage in performance analysis in a virtualized cloud environment.