Massively parallel Fourier-optics based processor

Volker J. Sorger

doi:10.1117/12.2568260

20 August 2020 Massively parallel Fourier-optics based processor

Volker J. Sorger

Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 114690K (2020) https://doi.org/10.1117/12.2568260
Event: SPIE Nanoscience + Engineering, 2020, Online Only

Abstract

Performing feature extractions in convolution neural networks for deep-learning tasks is computational expensive in electronics. Fourier optics allows convolutional filtering via dot-product multiplication in the Fourier domain similar to the distributive law in mathematics. Here we experimentally demonstrate convolutional filtering exploiting massive parallelism (10^6 channels, 8-bit at 1kHz) of digital mirror display technology, thus enabling 250 TMAC/s. An FPGA-PCIe board controls the ‘weights’ and handles the data I/O, whereas a high-speed camera detects the inverse-Fourier transformed (2nd lens) data. Gen-1 processes with a total delay (including I/O) of ~1ms, while Gen-2 at 1^-10ns leveraging integrated photonics at 10GHz and changing the front-end I/O to a joint-transform-correlator (JTC). These processors are suited for image/pattern recognition, super resolution for geolocalization, or real-time processing in autonomous vehicles or military decision making.

Conference Presentation

Citation Download Citation

Volker J. Sorger "Massively parallel Fourier-optics based processor", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 114690K (20 August 2020); https://doi.org/10.1117/12.2568260

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