Dynamic Computing in Memory (DCIM) in Resistive Crossbar Arrays

Abstract

With Von-Neumann computing struggling to match the energy-efficiency of biological systems, there is pressing need to explore alternative computing models. Recent experimental studies have revealed that Resistive Random Access Memory (RRAM) is promising alternative for DRAM. Resistive crossbar arrays possess many promising features that can not only enable high-density and low-power storage but also non Von-Neumann compute models. Most recent works focus on dot product operation with RRAM crossbar arrays, and therefore are not flexible to implement various logical functions. We propose a low-power dynamic computing in memory system which can implement various functions in Sum of Product (SOP) form in RRAM crossbar array architecture. We evaluate the proposed technique by performing simulation over wide range of MCNC benchmarks. Simulation results show 1.42X and 20X latency improvement as well as 2.6X and 12.6X power saving compared to static and MAGIC computing in memory methods.