Towards Quality-Driven Approximate Software Generation for Accurate Hardware: Work-in-Progress

Many existing processor-based systems, especially using off-the-shelf components, cannot afford hardware modifications to embrace different approximate computing techniques proposed by the research community. In that case, it is mainly at the software level where error resiliency can be exploited efficiently. Although a multitude of approximate techniques can be applied at software level, they have been presented in isolation and little has been done to report their combined usage on different types of applications amenable to approximations. We present here AxSWGen, an automated quality-driven methodology to jointly explore and apply multiple approximate techniques to error-tolerant sections of applications. AxSWGen is implemented using LLVM compiler infrastructure. We present results of automated approximate software generated with AxSWGen and executed on a RISC-V processor (SiFive HiFive1 board), achieving up to 50% energy reduction for a 5% image degradation for an approximate Gaussian filter.