diffusion model

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MTDiff: A Multi-Task Diffusion Accelerator With Bandwidth-Aware Memory Partition and Efficient Digital Compute-in-Memory

MTDiff: A Multi-Task Diffusion Accelerator With Bandwidth-Aware Memory Partition and Efficient Digital Compute-in-Memory 150 150
Author(s): Jiaqi Zhou, Yiqi Jing, Yiyang Sun, Siyuan He, Le Ye, Tianyu Jia

Abstract:

Initially applied to image synthesis, diffusion models have rapidly expanded into various content generation tasks, such as 3-D scene reconstruction and video generation, due to the superior generative quality. Based on our observations, the imbalanced operational intensities across diffusion model layers lead to suboptimal hardware utilization due to inadequate bandwidth …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 14
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3718715
Publisher: IEEE

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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

View on IEEE Xplore

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