Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

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 timeconsuming 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 multiobjective 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. CCS CONCEPTS• Computer systems organization → Embedded systems; • Software and its engineering → Compilers; • Computing methodologies → Modeling methodologies; • Mathematics of computing → Discrete optimization.