Exact In-Memory Multiplication Based on Deterministic Stochastic Computing

Abstract

Memristors offer the ability to both store and process data in memory, eliminating the overhead of data transfer between memory and processing unit. For data-intensive applications, developing efficient in-memory computing methods is under investigation. Stochastic computing (SC), a paradigm offering simple execution of complex operations, has been used for reliable and efficient multiplication of data in-memory. Current SC-based in-memory methods are incapable of producing accurate results. This work, to the best of our knowledge, develops the first accurate SC-based in-memory multiplier. For logical operations, we use Memristor-Aided Logic (MAGIC), and to generate bit-streams, we propose a novel method, which takes advantage of the intrinsic properties of memristors. The proposed design improves the speed and reduces the memory usage and energy consumption compared to the State-of-the-Art (SoA) accurate in-memory fixed-point and off-memory SC multipliers.