Energy Optimal Task Scheduling with Normally-Off Local Memory and Sleep-Aware Shared Memory with Access Conflict

The rapid development of the Real-Time and Embedded System (RTES) has increased the requirement on the processing capabilities of sensors, mobiles and smart devices, etc. Meanwhile, energy efficiency techniques are in desperate need as most devices in RTES are battery powered. Following the above trends, this work explores the memory system energy efficiency for a general multi-core architecture. This architecture integrates a local memory in each processing core, with a large off-chip memory shared among multiple cores. Decisions need to be made on whether tasks will be executed with the shared memory or the local memory to minimize the total energy consumption within real-time constraints. This paper proposes optimal schemes as well as a polynomial-time approximation algorithm with constant ratio. The problem complexity analysis for different task and system models is also presented. Experimental results show that the proposed approximation scheme performs close to the optimal solution in average.