AI accelerators

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Denim: Heterogeneous Compute-in-Memory Accelerator Exploiting Denoising–Similarity for Diffusion Models

Denim: Heterogeneous Compute-in-Memory Accelerator Exploiting Denoising–Similarity for Diffusion Models 150 150
Author(s): Ruiqi Guo, Lei Wang, Xiaofeng Chen, Keyi Jiang, Zhiheng Yue, Huiming Han, Yang Wang, Fengbin Tu, Shaojun Wei, Yang Hu, Shouyi Yin

Abstract:

Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the main drawbacks of diffusion models is that the image generation process is expensive. Large image-to-image networks have to be applied multiple times in order to iteratively optimize the …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 15
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3684745
Publisher: IEEE

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A 3-D HBI Compliant 1.536 TB/s/mm2 Bandwidth Scalable Attention Accelerator With 22.5-GOPS Throughput High Speed SoftMax for Quantized Transformers in Intel 3

A 3-D HBI Compliant 1.536 TB/s/mm2 Bandwidth Scalable Attention Accelerator With 22.5-GOPS Throughput High Speed SoftMax for Quantized Transformers in Intel 3 150 150
Author(s): Prerna Budhkar, Mirco Sciulli, Srivatsa Rangachar Srinivasa, Gauthaman Murali, Ragh Kuttappa, Paolo Aseron, Trang Nguyen, Vinayak Honkote, Tanay Karnik

Abstract:

This letter presents a novel hardware accelerator compatible with <3- $\mu $ m pitch 3-D Cu-Cu hybrid bonding interconnect (HBI) technology, particularly designed to efficiently execute multihead attention (MHA) of encoder transformer models. We present an accelerator that addresses performance losses due to low precision models by incorporating specialized hardware optimizations …

Published in: IEEE Solid-State Circuits Letters
Page(s): 69 – 72
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3659575
Publisher: IEEE

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