List Scheduling in Embedded Systems under Memory Constraints

Video decoding and image processing in embedded systems are subject to strong resource constraints, particularly in terms of memory. List-scheduling heuristics with static priorities (HEFT, SDC, etc.) being the often-cited solutions due to both their good performance and their low complexity, we propose a method aimed at introducing the notion of memory into them. Moreover, we show that through appropriate adjustment of task priorities and judicious resort to insertion-based policy, speedups up to 20% can be achieved. Lastly, we show that our technique allows to prevent deadlock and to substantially reduce the required memory footprint compared to classic list-scheduling heuristics.