MAMOT: Memory-Aware Mapping Optimization Tool for MPSoC

Mapping applications onto multiprocessor system-on-chip (MPSoC) devices is a well-known and complex optimization problem, receiving large interest in recent years. Diverse frameworks for mapping optimization have been developed, that typically distribute application tasks to available processors while optimizing one or more objectives such as performance and energy consumption. However, even though the memory subsystem is a resource that contributes drastically to the overall performance and energy consumption of the MPSoC, no mapping optimization framework is considering it so far. This paper addresses this challenge, and investigates the effect of memory hierarchies for MPSoC mapping. A memory-aware mapping optimization tool (that we refer to as MAMOT) has been developed for this purpose. We primarily focus on heterogeneous MPSoCs with heterogeneous memory hierarchies. Our evaluations show that considering memory mapping during MPSoC mapping optimization may reduce the application runtime up to 29.5% and its energy consumption up to 40%.