Kryptonite: Worst-Case Program Interference Estimation on Multi-Core Embedded Systems

Abstract

Due to the low costs and energy needed, cyber-physical systems are adopting multi-core processors for their embedded computing requirements. In order to guarantee safety when the application has real-time constraints, a critical requirement is to estimate the worst-case interference from other executing programs. However, the complexity of multi-core hardware inhibits precisely determining the Worst-Case Program Interference. Existing solutions are either prone to overestimate the interference or are not scalable to different hardware sizes and designs. In this paper we present Kryptonite , an automated framework to synthesize Worst-Case Program Interference (WCPI) environments for multi-core systems. Fundamental to Kryptonite is a set of tiny hardware-specific code gadgets that are crafted to maximize interference locally. The gadgets are arranged using a greedy approach and then molded using a Reinforcement Learning algorithm to create the WCPI environment. We demonstrate Kryptonite on the automotive grade Infineon AURIX TC399 processor with a wide range of programs that includes a commercial real-time automotive application. We show that, while being easily scalable and tunable, Kryptonite creates WCPI environments increasing the runtime by up to 58% for benchmark applications and 26% for the automotive application.