2026-07-25T06:21:07Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:22907 2025-10-02T12:07:44Z ddc:004 open_access

System-Level Timing Performance Estimation Based on a Unifying HW/SW Performance Metric Muttillo, Vittoriano Stoico, Vincenzo Valente, Giacomo Santic, Marco Pomante, Luigi Frigioni, Daniele embedded systems hw/sw co-design performance estimation lasso machine learning The rapidly increasing complexity of embedded systems and the critical impact of non-functional requirements demand the adoption of an appropriate system-level HW/SW co-design methodology. This methodology tries to satisfy all design requirements by simultaneously considering several alternative HW/SW implementations. In this context, early performance estimation approaches are crucial in reducing the design space, thereby minimizing design time and cost. To address the challenge of system-level performance estimation, this work presents and formalizes a novel approach based on a unifying HW/SW performance metric for early execution time estimation. The proposed approach estimates the execution time of a C function when executed by different HW/SW processor technologies. The approach is validated through an extensive experimental study, demonstrating its effectiveness and efficiency in terms of estimation error (i.e., lower than 10%) and estimation time (close to zero) when compared to existing methods in the literature. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Vittoriano Muttillo and Vincenzo Stoico and Giacomo Valente and Marco Santic and Luigi Pomante and Daniele Frigioni 2025 Is Part Of OASIcs, Volume 127, 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.PARMA-DITAM.2025.3 urn:nbn:de:0030-drops-229071 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.3 eng https://creativecommons.org/licenses/by/4.0/legalcode