Cycle-Oriented Dynamic Approximation: Architectural Framework to Meet Performance Requirements

Approximate computing achieves shorter execution times and reduced energy consumption in areas where precise computation written in a program is not essential to meet a goal. When applying the approximations, it is vital to satisfy the required quality-of-service (QoS) (execution time) and quality-of-results (QoR) (output accuracy). Existing methods have difficulty in maintaining a constant QoS or impose a burden on programmers. In this study, we propose the Cycle-oriented Dynamic Approximation (CODAX) algorithms and processor architecture that minimize the burden on the programmer and maintain the execution time close to the required QoS while providing the user with an option to satisfy their QoR requirement. CODAX operates based on a threshold that indicates the maximum number of cycles available for one loop iteration. The threshold automatically increases or decreases at runtime to bring the total number of elapsed cycles close to the required QoS. Furthermore, CODAX allows the user to change the threshold to indirectly guarantee the required QoR. Our simulation revealed that CODAX brought the actual number of executed cycles close to the expected number for four workloads.