학술논문
Ternary In-Memory MAC Accelerator With Dual-6T SRAM Cell for Deep Neural Networks
Document Type
Conference
Author
Source
2022 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) Circuits and Systems (APCCAS), 2022 IEEE Asia Pacific Conference on. :246-250 Nov, 2022
Subject
Language
Abstract
In-memory computing (IMC) based on static random access memory (SRAM) is a promising solution to enable highly energy-efficient multiply-accumulate (MAC) operations for machine learning accelerators. In this paper, an in-SRAM computing technique is proposed by using a dual-six-transistor (dual-6T) SRAM cell. The dual-6T SRAM cell is composed of two conventional-6T-SRAM-cell-like 6T cells with split wordlines, achieving a compact array layout. With specialized coding, the dual-6T SRAM circuit is one of the few in-memory accelerators which support parallel MAC operations with both ternary activation and ternary weight. A $128\times 64$ memory array is implemented in a 55-nm low-power CMOS technology. Due to the compact bitcell topology and smart coding, the proposed dual-6T memory array achieves up to 635 TOPS/W energy efficiency @ 100 MHz and 38.84 TOPS/mm 2 peak area efficiency @ 350 MHz, which is competitive among the state-of-the-art in-memory computing MAC accelerators.