IMA-GNN: In-Memory Acceleration of Centralized and Decentralized Graph Neural Networks at the Edge

Author:

Morsali Mehrdad1ORCID,Nazzal Mahmoud1ORCID,Khreishah Abdallah1ORCID,Angizi Shaahin1ORCID

Affiliation:

1. New Jersey Institute of Technology, Newark, NJ, USA

Funder

National Science Foundation

Publisher

ACM

Reference26 articles.

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2. MR-PIPA: An Integrated Multilevel RRAM (HfOx)-Based Processing-In-Pixel Accelerator;Abedin Minhaz;IEEE JxCDC,2022

3. Shaahin Angizi , Sepehr Tabrizchi , and Arman Roohi . 2022 . Pisa: A binary-weight processing-in-sensor accelerator for edge image processing. arXiv preprint arXiv:2202.09035 (2022). Shaahin Angizi, Sepehr Tabrizchi, and Arman Roohi. 2022. Pisa: A binary-weight processing-in-sensor accelerator for edge image processing. arXiv preprint arXiv:2202.09035 (2022).

4. Nagadastagiri Challapalle , Karthik Swaminathan , Nandhini Chandramoorthy , and Vijaykrishnan Narayanan . 2021. Crossbar based processing in memory accelerator architecture for graph convolutional networks . In ICCAD. IEEE , 1--9. Nagadastagiri Challapalle, Karthik Swaminathan, Nandhini Chandramoorthy, and Vijaykrishnan Narayanan. 2021. Crossbar based processing in memory accelerator architecture for graph convolutional networks. In ICCAD. IEEE, 1--9.

5. Ligang Gao et al. 2012. Analog-input analog-weight dot-product operation with Ag/a-Si/Pt memristive devices. In VLSI-SoC. IEEE 88--93. Ligang Gao et al. 2012. Analog-input analog-weight dot-product operation with Ag/a-Si/Pt memristive devices. In VLSI-SoC. IEEE 88--93.

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