A Floating-Point 6T SRAM In-Memory-Compute Macro Using Hybrid-Domain Structure f

Abstract

Advanced artificial intelligence edge devices are expected to support floating-point (FP) multiply and accumu- lation operations while ensuring high energy efficiency and high inference accuracy. This work presents an FP compute-in- memory (CIM) macro that exploits the advantages of computing in the time, digital, and analog-voltage domain for high energy efficiency and accuracy. This work employs: 1) a hybrid-domain macrostructure to enable the computation of both the exponent and mantissa with