A parameterized compositional multi-dimensional multiple-choice knapsack heuristic for CMP run-time management

Modern embedded systems typically contain chip-multiprocessors (CMPs) and support a variety of applications. Applications may run concurrently and can be started and stopped over time. Each application may typically have multiple feasible configurations, trading off quality aspects (energy consumption, audio-visual quality) with resource usage for various types of resources. Overall system quality needs to be guaranteed and optimized at all times. This leads to the need for a run-time management solution that selects an appropriate system configuration from all the application configurations of active applications. This run-time management problem can be phrased as a multi-dimensional multiple-choice knapsack (MMKP) problem. We present a compositional heuristic to solve MMKP, that due to the compositionality is better suited to CMP run-time management than existing heuristics that are all not compositional. Our heuristic outperforms the best-known heuristic to date. The heuristic is parameterized, leading to the additional advantage that it allows to trade off execution time vs. solution quality, and to bound the time needed to compute a solution. The latter makes it particularly well-suited for resource-constrained embedded platforms.