|Title: Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation. <em>In Proceedings of the 30th International Conference on Real-Time Networks and Systems (RTNS)</em>|
|Written by: Shashank Jadhav and Heiko Falk|
|in: June (2022).|
|on pages: 162-172|
|Address: Paris / France|
|how published: 22-80 JaFa22 RTNS|
Note: sjadhav, hfalk, ESD, WCC
Abstract: Worst-Case Execution Time (WCET) is the most important design criterion in the domain of hard real-time systems. Most embedded systems also need to satisfy additional design criteria like, e.g., energy consumption. Performing WCET and energy analyses statically at compile-time can be time-consuming. Consequently, minimizing WCET and energy consumption of the code at the compiler level using multi-objective optimization can be a time-consuming process. In this paper, we propose an approximation model to quickly approximate the WCET and energy consumption of the code at compile-time. Instead of using traditional WCET and energy analyses, we exploit this approximation model to perform ScratchPad Memory (SPM) allocation-based multi-objective optimization. Furthermore, we solve the multi-objective optimization problem using metaheuristic algorithms and explore the trade-offs between WCET and energy consumption. Using the proposed approximation model, we achieved, on average, a 94.12% reduction in compilation time and maintained the quality of the Pareto optimal solutions while performing the multi-objective optimization. Furthermore, the approximation error while using the proposed approximation model was in an acceptable range of 2% - 4% on average.