Energy-efficient computing using adaptive table lookup based on nonvolatile memories

Table lookup based function computation can significantly save energy consumption. However existing table lookup methods are mostly used in ASIC designs for some fixed functions. The goal of this paper is to enable table lookup computation in general-purpose processors, which requires adaptive lookup tables for different applications. We provide a complete design flow to support this requirement. We propose a novel approach to build the reconfigurable lookup tables based on emerging nonvolatile memories (NVMs), which takes full advantages of NVMs over conventional SRAMs and avoids the limitation of NVMs. We provide compiler support to optimize table resource allocation among functions within a program. We also develop a runtime table manager that can learn from history and improve its arbitration of the limited on-chip table resources among programs.