AxPIKE: instruction-level injection and evaluation of approximate computing

Abstract

Representing the interaction between accurate and approximate hardware modules at the architecture level is essential to understand the impact of Approximate Computing in a general-purpose computing scenario. However, extensive effort is required to model approximations into a baseline instruction-level simulator and collect its execution metrics. In this work, we present the AxPIKE ISA simulation environment, a tool that allows designers to inject models of hardware approximation at the instruction level and evaluate their impact on the quality of results. AxPIKE embeds a high-level representation of a RISC-V system and produces a dedicated control mechanism, that allows the simulated software to manage the approximate behavior of compatible execution scenarios. The environment also provides detailed execution statistics that are forwarded to dedicated tools for energy accounting. We apply the AxPIKE environment to inject integer multiplication and memory access approximations into different applications and demonstrate how the generated statistics are translated into energy-quality trade-offs.