Efficient floating point precision tuning for approximate computing

Nhut-Minh Ho, Elavarasi Manogaran, Weng-Fai Wong, Asha Anoosheh

Abstract: This paper presents an automatic tool-chain that efficiently computes the precision of floating point variables down to the bit level of the mantissa. Our toolchain uses a distributed algorithm that can analyze thousands of variables. We successfully used the tool to transform floating point signal processing programs to their arbitrary precision fixed-point equivalent, obtaining about 82% and 66% average reduction in resources when compared to the double precision and single precision versions, respectively.