Memory-aware mapping and scheduling of tasks and communications on many-core SoC

This paper presents an approach to automatic task mapping, scheduling, and communication routing on a many-core SoC, considering the trade-offs between two different communication types-message passing and shared memory-for the communication routing in order to optimize the energy consumption or performance. To solve the optimization problem, the approach uses the quantum-inspired evolutionary algorithm. For the scheduling of the tasks with backward dependencies, it uses the iterative modulo scheduling technique. Experiments with random task graphs as well as real applications show the effectiveness of the proposed approach.