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Scaling-CIM: An eDRAM-based In-Memory-Computing Accelerator with Dynamic-Scaling ADC for SQNR-Boosting and Layer-wise Adaptive Bit-Truncation | IEEE Conference Publication | IEEE Xplore

Scaling-CIM: An eDRAM-based In-Memory-Computing Accelerator with Dynamic-Scaling ADC for SQNR-Boosting and Layer-wise Adaptive Bit-Truncation


Abstract:

This paper presents Scaling-CIM, an energy-efficient eDRAM-IMC with the dynamic-scaling readout for SQNR boosting and ADC overhead reduction. Dynamic Scaling ADC boosts S...Show More

Abstract:

This paper presents Scaling-CIM, an energy-efficient eDRAM-IMC with the dynamic-scaling readout for SQNR boosting and ADC overhead reduction. Dynamic Scaling ADC boosts SQNR of multi-bit operation even with low-bit ADC. Adaptive analog bit-parallel accumulation reduces the redundant ADC operation. Also, layer-wise adaptive bit-truncation search further enhances efficiency on benchmarks. The accelerator is fabricated in 28nm CMOS technology and occupies 2.03\mathrm{m}\mathrm{m}^{2} die area. It achieves 39.7 TOPS/W energy efficiency on ResNet-18 benchmark and 6.8\times higher efficiency FoM compared to the previous IMC-based accelerator.
Date of Conference: 11-16 June 2023
Date Added to IEEE Xplore: 24 July 2023
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Conference Location: Kyoto, Japan

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