A 40-nm, 64-Kb, 56.67 TOPS/W Voltage-Sensing Computing-In-Memory/Digital RRAM Macro Supporting Iterative Write With Verification and Online Read-Disturb Detection

Computing-in-memory (CIM) architectures have gained importance in achieving high-throughput energy-efficient artificial intelligence (AI) systems. Resistive RAM (RRAM) is a promising candidate for CIM architectures due to a multiply-and-accumulate (MAC)-friendly structure, high bit density, compatib...

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Veröffentlicht in:IEEE journal of solid-state circuits 2022-01, Vol.57 (1), p.68-79
Hauptverfasser: Yoon, Jong-Hyeok, Chang, Muya, Khwa, Win-San, Chih, Yu-Der, Chang, Meng-Fan, Raychowdhury, Arijit
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Sprache:eng
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Zusammenfassung:Computing-in-memory (CIM) architectures have gained importance in achieving high-throughput energy-efficient artificial intelligence (AI) systems. Resistive RAM (RRAM) is a promising candidate for CIM architectures due to a multiply-and-accumulate (MAC)-friendly structure, high bit density, compatibility with a CMOS process, and nonvolatility. Notwithstanding the advancement of RRAM technology, the reliability of an RRAM array hinders the spread of RRAM applications such that a circuit-technology joint approach is necessary to attain reliable RRAM-based CIM architectures. This article presents a 64-kb hybrid CIM/digital RRAM macro supporting: 1) active-feedback-based voltage-sensing read (RD) to enable 1-8-b programmable vector-matrix multiplication under a low-resistance ratio of the high-resistance state to the low-resistance state in an RRAM array; 2) iterative write with verification to secure a tight resistance distribution; and 3) online RD-disturb detection in the background during CIM. The test chip fabricated in a 40-nm CMOS and RRAM process achieves a peak energy efficiency of 56.67 TOPS/W while demonstrating the eight-bitline hybrid CIM/digital MAC operation with 1-8-b inputs and weights and 20-b outputs without quantization.
ISSN:0018-9200
1558-173X
DOI:10.1109/JSSC.2021.3101209