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A 64 Kb Reconfigurable Full-Precision Digital ReRAM-Based Compute-In-Memory for Artificial Intelligence Applications

Vishal Sharma, Hyunjoon Kim, Tony Tae-Hyoung Kim

2022IEEE Transactions on Circuits and Systems I Regular Papers28 citationsDOI

Abstract

This work presents a fully-digital 64 Kb non-volatile ReRAM based compute-in-memory (CIM) macro for the modern artificial intelligence (AI) edge devices, using 65 nm technology. This digital CIM architecture effectively removes the analog-design issues, related to process variations, noise susceptibility, and data-conversion overhead. Hence, it offers no accuracy loss and high energy-efficiency for the computation. To incorporate the digital computation, a novel NAND logic based 3.25T1R bitcell is proposed. The digital behaviour of this cell makes it superior to the conventional 1T1R based analog bitcell. Also, with the inherent non-volatility of ReRAM, the proposed cell can be a good substitute for SRAM-based CIM architectures with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.62\times $ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.96\times $ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.96\times $ </tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5.12\times $ </tex-math></inline-formula> lower area than the XNOR-based 12T, Twin-8T, 8T, and 6T SRAM cell respectively. Moreover, the proposed CIM architecture allows full reconfigurabiliy from 1 to 16b precision for both input and weight. It also allows activating any number of parallel inputs, ranging from 1 to 128. According to simulation results, the proposed macro successfully operates up to 166.6 MHz for 1/8/15b input/weight/output precision and achieves 27.28 TOPS/W without any accuracy loss. Removing sense amplifiers for the ReRAM mode of the proposed work claims additional area and power savings.

Topics & Concepts

Computer scienceComputationNotationAlgorithmArithmeticMathematicsAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesSemiconductor materials and devices
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