OISA: Architecting an Optical In-Sensor Accelerator for Efficient Visual Computing
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
Targeting vision applications at the edge, in this work, we systematically explore and propose a high-performance and energy-efficient Optical In-Sensor Accelerator architecture called OISA for the first time. Taking advantage of the promising efficiency of photonic devices, the OISA intrinsically implements a coarse-grained convolution operation on the input frames in an innovative minimum-conversion fashion in low-bit-width neural networks. Such a design remarkably reduces the power consumption of data conversion, transmission, and processing in the conventional cloud-centric architecture as well as recently-presented edge accelerators. Our device-to-architecture simulation results on various image data-sets demonstrate acceptable accuracy while OISA achieves 6.68 TOp/s/W efficiency. OISA reduces power consumption by a factor of 7.9 and 18.4 on average compared with existing electronic in-/near-sensor and ASIC accelerators.
Identifier
85196481554 (Scopus)
ISBN
[9798350348590]
Publication Title
Proceedings -Design, Automation and Test in Europe, DATE
ISSN
15301591
Grant
2216772
Fund Ref
Semiconductor Research Corporation
Recommended Citation
Morsali, Mehrdad; Tabrizchi, Sepehr; Najafi, Deniz; Imani, Mohsen; Nikdast, Mahdi; Roohi, Arman; and Angizi, Shaahin, "OISA: Architecting an Optical In-Sensor Accelerator for Efficient Visual Computing" (2024). Faculty Publications. 971.
https://digitalcommons.njit.edu/fac_pubs/971