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arXiv · 2409.02689

Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device

Jun Ji·Zichen Xi·Bernadeta R. Srijanto·Ivan I. Kravchenko·Ming Jin·Wenjie Xiong·Linbo Shao
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Abstract

Multiply-accumulation (MAC) is a crucial computing operation in signal processing, numerical simulations, and machine learning. This work presents a scalable, programmable, frequency-domain parallel computing leveraging gigahertz (GHz)-frequency acoustic-wave nonlinearities. By encoding data in the frequency domain, a single nonlinear acoustic-wave device can perform a billion arithmetic operations simultaneously. A single device with a footprint of 0.03 mm$^2$ on lithium niobate (LN) achieves 0.0144 tera floating-point operations per second (TFLOPS), leading to a computing area density of 0.48 TFLOPS/mm$^2$ and a core power efficiency of 0.14 TFLOPS/Watt. As applications, we demonstrate multiplications of two 16-by-16 matrices and convolutional imaging processing of 128-by-128-pixel photos. Our technology could find versatile applications in near-sensor signal processing and edge computing.

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Jun Ji, Zichen Xi, Bernadeta R. Srijanto, Ivan I. Kravchenko, Ming Jin, Wenjie Xiong, Linbo Shao. 2024-09-04. Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device. https://arxiv.org/abs/2409.02689

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