Application-specific shared last-level cache optimization for low-power embedded systems

Modern embedded systems favor the chip multiprocessor frame to achieve higher performance, but they are restricted by the inefficient cache hierarchies. Typically, the accessing interference and improper allocation in last-level cache (LLC) shared by multiprocessors cause significant energy consumption and performance depression. In this paper, we propose a configurable and partitioned cache hierarchy where an energy-efficient runtime mechanism can well manage the shared LLC to meet application programs. This mechanism utilizes the repeated behaviors in hot subroutines of application and selects the proper partition intervals. Then, a low-power metric based configurable scheme is employed to explore the optimal allocation of given cache resources. Thus, we can provide each core with the optimal allocation information to dynamically partition the shared LLC during runtime. Experimental results for a quad-core system using the SPEC2006 benchmarks show that the cache access energy can be reduced by on average 32.5 percent compared to the equal partition scheme only with 1.3 percent performance off.