Design-Time memory subsystem optimization for low-power multi-core embedded systems

Abstract

Embedded multi-core systems are increasingly in use. As established single-core design methodologies are often not applicable out of the box, novel design-Time optimization methods are required in order to manage real-Time characteristics, predictability, or tight constraints with respect to energy consumption or system performance. With focus on the memory subsystem in a multi-core embedded system, this paper proposes an optimization workflow for the application-specific optimal binding of code and data to memory instances, efficient handling and scheduling of available memory low-power modes, and the automated and transparent integration of these optimization results on the software level. Presented optimization algorithms are realized as integer linear programs; code modification and generation are implemented on the basis of LLVM. Experimental results for an ARM-based quad-core platform with SRAM memory subsystem, consisting of core-local scratchpad memories and global shared memory, prove the efficiency of our method in terms of energy consumption when compared to a system using direct-mapped caches, but also in comparison with a state-of-The-Art scratchpad mapping heuristic.