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논문 기본 정보

저자정보
(Korea Advanced Institute of Science and Technology) (Korea Advanced Institute of Science and Technology) (Korea Advanced Institute of Science and Technology) (Korea Advanced Institute of Science and Technology) (Korea Advanced Institute of Science and Technology)
저널정보
대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.25 No.4
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    초록·키워드

    This paper introduces a novel computing-in-memory (CIM) processor designed for processing deep neural networks (DNNs) with mixed precision, overcoming the limitations of previous CIM architectures that employed bit-serial operations for multi-bit data. The proposed solution, termed the mixed-mode mixed-precision CIM (mixed-CIM) processor, integrates two main features for enhanced energy efficiency: first, the mixed-CIM architecture, which improves energy efficiency by 55.5% compared to prior approaches; second, a digital CIM approach for in-memory multiply-and-accumulate (MAC) operations that boosts throughput by 41.3%. The processor, developed using 28 nm CMOS technology with an area of 1.96 mm², achieves an energy efficiency of 85.7 TOPS/W while maintaining 77.4% accuracy on CIFAR100 with ResNet18.

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