ePAPI: Performance Application ProgrammingInterface for Embedded Platforms

Performance Monitoring Counters (PMCs) have been traditionally used in the mainstream computing domain to perform debugging and optimization of software performance. PMCs are increasingly considered in embedded time-critical domains to collect in-depth information, e.g. cache misses and memory accesses, of software execution time on complex multicore platforms. In main-stream platforms, standardized specifications and applications like the Performance Application Programming Interface (PAPI) and perf have been proposed to deal with variable PMC support across platforms, by providing a shared interface for configuring and collecting traceable events. However, no equivalent solution exists for embedded critical processors for which the user is required to deal with low-level, platform-specific, and error-prone manipulation of PMC registers. In this paper, we address the need for a standardized PMC interface in the embedded domain, especially in view to support timing characterization of embedded platforms. We assess the compatibility of the PAPI interface with the PMC support available on the AURIX TC297, a reference automotive platform, and we implement and validate ePAPI, the first functionally-equivalent and low-overhead implementation of PAPI for the considered embedded platform.This work has been partially supported by the Spanish Ministry of Economy and Competit-iveness (MINECO) under grant TIN2015-65316-P, the European Research Council (ERC) under theEuropean Union’s Horizon 2020 research and innovation programme (grant agreement No. 772773),the European Union’s Regional Development Fund (ERDF) within the framework of the ERDF(FEDER) program in Catalonia 2014-2020 under the grant SDESI (2016 PROD00115), and theHiPEAC Network of Excellence. Jaume Abella and Enrico Mezzetti have been partially supportedby MINECO under Ramon y Cajal and Juan de la Cierva-Incorporación postdoctoral fellowshipsnumber RYC-2013-14717 and IJCI-2016-27396 respectivelyPeer Reviewe