Minimum Effort Design Space Subsetting for Configurable Caches

Configurable caches can significantly reduce energy consumption by adapting the system´s cache configuration to the applications´ specific requirements to meet system design and optimization goals. However, large configuration design spaces require prohibitive design space exploration time (e.g., due to lengthy design space analyses, simulations, and/or evaluations) to determine the best configuration given these requirements and goals. To significantly reduce design space exploration time, we evaluate a design space subsetting method that removes energy-redundant configurations (i.e., configurations that provide similar energy savings as other configurations), thus significantly reducing the design space while still providing high-quality, energy-saving configurations. Prior work verified design space subsetting´s efficacy, however, prior work required extensive design-time effort and complete a priori knowledge of the system´s anticipated applications. In this work, we alleviate these limitations and significantly broaden the usability of design space subsetting. Results show that complete a priori knowledge of the anticipated applications is not necessary, and only a small set of applications representative of the anticipated applications´ general domains (or applications with similar requirements) is sufficient to provide energy savings within 5.6% of the complete, unsubsetted design space.