Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917778359844864 |
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| author | Ji, Jun Xi, Zichen Srijanto, Bernadeta R. Kravchenko, Ivan I. Jin, Ming Xiong, Wenjie Shao, Linbo |
| author_facet | Ji, Jun Xi, Zichen Srijanto, Bernadeta R. Kravchenko, Ivan I. Jin, Ming Xiong, Wenjie Shao, Linbo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_02689 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device Ji, Jun Xi, Zichen Srijanto, Bernadeta R. Kravchenko, Ivan I. Jin, Ming Xiong, Wenjie Shao, Linbo Applied Physics Emerging Technologies 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. |
| title | Frequency-domain Parallel Computing Using Single On-Chip Nonlinear Acoustic-wave Device |
| topic | Applied Physics Emerging Technologies |
| url | https://arxiv.org/abs/2409.02689 |