A 8-b-Precision 6T SRAM Computing-in-Memory Macro Using Segmented-Bitline Charge-Sharing Scheme for AI

Abstract

Advances in static random access memory (SRAM)- CIM devices are meant to increase capacity while improving energy efficiency (EF) and reducing computing latency ( T AC). This work presents a novel SRAM-CIM structure using: 1) a segmented-bitline charge-sharing (SBCS) scheme for multiply-and-accumulate (MAC) operations with low energy consumption and a consistently high signal margin across MAC values; 2) a bitline-combining (BL-CMB) scheme to reduce the number of analog-to-digital converters (ADCs) and, thereby, pro- vide options in determining a tradeoff between EF and inference accuracy; 3) a source-injection local-multiplication cell (SILMC) connected to two types of global-bitline-switch to support the SBCS and BL-CMB schemes with consistent signal margin against process variation in transistors; and 4) prioritized- hybrid ADC to suppress area and power overhead for analog readout operations. We fabricated a 28-nm 384-kb SRAM-CIM macro using foundry-provided compact-6T cells supporting MAC operations with 16 accumulations of 8-b input and 8-b weight with near-full precision output (20 b). This macro achieved T AC of 7.2 ns and EF of 22.75 TOPS/W performing 8-b-MAC operations. Manuscript received 12 March 2022; revised 10 June 2022; accepted 9 August 2022. Date of publication 21 September 2022; date of current version 24 February 2023. This article was approved by Associate Editor Vivek De. This work was supported in part by the Industrial Technology Research Institute (ITR