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MINOTAUR: A Posit-Based 0.42–0.50-TOPS/W Edge Transformer Inference and Training Accelerator

MINOTAUR: A Posit-Based 0.42–0.50-TOPS/W Edge Transformer Inference and Training Accelerator 150 150
Author(s): Kartik Prabhu, Robert M. Radway, Jeffrey Yu, Kai Bartolone, Massimo Giordano, Fabian Peddinghaus, Yonatan Urman, Win-San Khwa, Yu-Der Chih, Meng-Fan Chang, Subhasish Mitra, Priyanka Raina

Abstract:

Transformer models have revolutionized natural language processing (NLP) and enabled many new applications, but are challenging to deploy on resource-constrained edge devices due to their high computation and memory demands. We present MINOTAUR, an edge system-on-chip (SoC) for inference and fine-tuning of Transformer models with all memory on the chip. …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1311 – 1323
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3545731
Publisher: IEEE

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Cryogenic Hyperdimensional In-Memory Computing Using Ferroelectric TCAM

Cryogenic Hyperdimensional In-Memory Computing Using Ferroelectric TCAM 150 150
Author(s): Shivendra Singh Parihar, Shubham Kumar, Swetaki Chatterjee, Girish Pahwa, Yogesh Singh Chauhan, Hussam Amrouch

Abstract:

Cryogenic operations of electronics present a significant step forward to achieve huge demand of in-memory computing (IMC) for high-performance computing, quantum computing, and military applications. Ferroelectric (FE) is a promising candidate to develop the complementary metal oxide semiconductor (CMOS)-compatible nonvolatile memories. Hence, in this work, we investigate the effectiveness …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 34 – 41
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3547797
Publisher: IEEE

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