OPTIMA: An Approach for Online Management of Cache Approximation Levels in Approximate Processing Systems

In this article, we present an approach for adjusting the approximation levels of the cache memories in the memory hierarchy of an approximate processing system. The technique, which is called online management of cache approximation level (OPTIMA), adjusts the approximation levels of the caches under a predefined accuracy constraint. OPTIMA may also be employed for multicore processors, which comprise cores with private and shared caches running applications with different error constraints. To reduce the energy consumption, OPTIMA determines the proper approximation level of each cache memory using heuristic algorithms in two main steps. In the first step, the approximate levels are adjusted to maximize the power efficiency by dropping the application accuracy to a level that still meets a desirable minimum output quality. In the second step, output accuracy variations due to input pattern changes are compensated by fine tuning. We suggest two algorithms (with different adjustment speeds of approximate levels) for the first step and another algorithm for the second step. To assess the efficacy of OPTIMA, we integrate it in the gem5 simulator and simulate some multiprocessor configurations by running eight approximate benchmarks. The results show that the proposed approach provides up to 44% power consumption reduction in the memory hierarchy.