An Activity Factor List for Energy Consumption of SRAM-based CIM Architectures

Abstract

In this paper, an activity factor list is generated using the NeuroSim V3.0 Compute-in-Memory (CIM) simulation program for MNIST-like datasets. This list provides necessary information for designers to make a pre-estimation on the energy consumption of SRAM-based CIM architectures. According to that, created list can shorten-up the process of CIM-design by eliminating repetitive simulations to estimate energy consumption for each individual dataset. In brief, we generated a switching activity factor list containing 5 different datasets for MLP neural networks to enlight energy consumption behaviour of SRAM-based CIM architectures.