  The approximate computing paradigm advocates for relaxing accuracy goals in
applications to improve energy-efficiency and performance. Recently, this
paradigm has been explored to improve the energy-efficiency of silicon photonic
networks-on-chip (PNoCs). Silicon photonic interconnects suffer from high power
dissipation because of laser sources, which generate carrier wavelengths, and
tuning power required for regulating photonic devices under different
uncertainties. In this paper, we propose a framework called ARXON to reduce
such power dissipation overhead by enabling intelligent and aggressive
approximation during communication over silicon photonic links in PNoCs. Our
framework reduces laser and tuning-power overhead while intelligently
approximating communication, such that application output quality is not
distorted beyond an acceptable limit. Simulation results show that our
framework can achieve up to 56.4% lower laser power consumption and up to 23.8%
better energy-efficiency than the best-known prior work on approximate
communication with silicon photonic interconnects and for the same application
output quality.
