Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device
<|reference_start|>Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device: 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.<|reference_end|>
@article{ji2024frequency-domain,
    title={Frequency-domain Parallel Computing Using Single On-Chip Nonlinear
  Acoustic-wave Device},
    author={Jun Ji, Zichen Xi, Bernadeta R. Srijanto, Ivan I. Kravchenko, Ming
  Jin, Wenjie Xiong, and Linbo Shao},
    journal={arXiv preprint arXiv:2409.02689},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.02689},
    primaryClass={physics.app-ph cs.ET}
}