Approximate computing

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An Approximate Digital CIM Macro With Low-Power Multiply-Add Units and Dynamic Sparse-Adaptive Configuring for Edge AI Inference

An Approximate Digital CIM Macro With Low-Power Multiply-Add Units and Dynamic Sparse-Adaptive Configuring for Edge AI Inference 150 150
Author(s): Xiaofeng Li, Yi Zhan, Purui Zhu, Rui Zhou, Jiayin Song, Heng You, Yumei Zhou, Shushan Qiao

Abstract:

This letter presents an approximate digital compute-in-memory (CIM) macro for low-power edge AI inference. It introduces three hierarchical innovations: 1) novel fused approximate multiply-add units (FAMUs) that reduces power and area consumption; 2) a bit-critical weight allocation architecture that optimally balances accuracy and hardware cost; and 3) a dynamic sparsity-adaptive configuration method to …

Published in: IEEE Solid-State Circuits Letters
Page(s): 45 – 48
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3652570
Publisher: IEEE

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IRIS: An Energy-Efficient Spatial Computing SoC for Real-Time Interactive Rendering and Modeling With Surface-Aware 3-D Gaussian Splatting

IRIS: An Energy-Efficient Spatial Computing SoC for Real-Time Interactive Rendering and Modeling With Surface-Aware 3-D Gaussian Splatting 150 150
Author(s): Seokchan Song, Seryeong Kim, Wonhoon Park, Jongjun Park, Sanghyuk An, Gwangtae Park, Minseo Kim, Hoi-Jun Yoo

Abstract:

The 3-D Gaussian splatting (3DGS), based on a machine learning-driven radiance field technique, is rapidly emerging as a next-generation solution in 3-D graphics. Owing to its short modeling time, computational simplicity, and high rendering quality, it is expected to replace traditional 3-D graphics on edge devices. However, its substantial memory …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 14
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3613707
Publisher: IEEE

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Fully Analog, Multi-Lag, RF Correlators for Code-Domain Radars Using Margin Propagation

Fully Analog, Multi-Lag, RF Correlators for Code-Domain Radars Using Margin Propagation 150 150
Author(s): Aswin Undavalli, Kareem Rashed, Abdul Rakib Hossain, Gert Cauwenberghs, Shantanu Chakrabartty, Arun Natarajan, Aravind Nagulu

Abstract:

We present a fully analog, multiplier-free, sampled-domain RF correlator to achieve high energy efficiency for radar workloads. The RF correlator employs a split-source follower architecture that leverages the margin propagation (MP) computing paradigm in the sampled domain. As a proof of concept, we implement a $256 \times 256$ fully analog cross correlator …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 16
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3602920
Publisher: IEEE

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