@conference {1378,
	title = {Software-Defined Events through PAPI},
	booktitle = {2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
	year = {2019},
	month = {2019-05},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Rio de Janeiro, Brazil},
	abstract = {PAPI has been used for almost two decades as an abstraction and standardization layer for profiling hardware-specific performance metrics. However, application developers-and profiling software packages-are quite often interested in information beyond hardware counters, such as the behavior of libraries used by the software that is being profiled. So far, accessing this information has required interfacing directly with the libraries on a case-by-case basis, or low-level binary instrumentation. In this paper, we introduce the new Software-Defined Event (SDE) component of PAPI which aims to enable PAPI to serve as an abstraction and standardization layer for events that originate in software layers as well. Extending PAPI to include SDEs enables monitoring of both types of performance events-hardware-and software-related events-in a uniform way, through the same consistent PAPI interface. Furthermore, implementing SDE as a PAPI component means that the new API is aimed only at the library developers who wish to export events from within their libraries. The API for reading PAPI events-both hardware and software-remains the same, so all legacy codes and tools that use PAPI will not only continue to work, but they will automatically be able to read SDEs wherever those are available. The goal of this paper is threefold. First, we outline our design decisions regarding the functionality we offer through the new SDE interface, and offer simple examples of usage. Second, we illustrate how those events can be utilized by different software packages, specifically, by showcasing their use in the task-based runtime PaRSEC, and the HPCG supercomputing benchmark. Third, we provide a thorough performance analysis of the overhead that results from monitoring different types of SDEs, and showcase the negligible overhead of using PAPI SDE even in cases of extremely heavy use.},
	doi = {https://doi.org/10.1109/IPDPSW.2019.00069},
	author = {Anthony Danalis and Heike Jagode and Thomas Herault and Piotr Luszczek and Jack Dongarra}
}
