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Coherent Photonic Vector Processor for Scalable and Efficient Optical Computing.

Rahimi Kari, Sadra (2024) Coherent Photonic Vector Processor for Scalable and Efficient Optical Computing. Master's Thesis, University of Pittsburgh. (Unpublished)

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Recent advancements in artificial intelligence (AI) have hinged on the capacity to train increasingly vast parameter sets within neural networks, a trend that has outpaced the computational capabilities of traditional digital hardware. This has led to a critical need for new computing paradigms that can simultaneously enhance computational efficiency and throughput. Photonic analog computing emerges as a promising solution to reduce latency and boost performance, particularly in addressing the memory-related challenges that underpin AI's success. This thesis presents an overview of the integration of optical and electrical memories with photonic hardware, underlining the pivotal role of memory technologies. It emphasizes the need for more efficient and compact memory for optical computing and presents an integrated coherent solution to process temporally multiplexed optical signals using a modular dot-product unit cell. We use these unit cells to demonstrate multiply accumulate operations on real- and complex-valued inputs using coherent detection and temporal integration. We then extend this to computing the covariance between stochastic bit streams which can be used to estimate correlation between data streams in the optical domain. Finally, we demonstrate a path to scaling up our platform to enable general matrix-matrix operations. This approach has the potential to enable highly efficient and scalable optical computing on-chip for a broad variety of AI applications.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Rahimi Kari, Sadrasar247@pitt.edusar247
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairYoungblood, Nathannathan.youngblood@pitt.edunay32
Thesis AdvisorYoungblood, Nathannathan.youngblood@pitt.edunay32
Committee MemberKubendran, Rajkumarrajkumar.ece@pitt.edurak196
Committee MemberLee, Inheeinhee.lee@pitt.eduinl13
Date: 11 January 2024
Date Type: Publication
Defense Date: 31 October 2023
Approval Date: 11 January 2024
Submission Date: 13 November 2023
Access Restriction: 1 year -- Restrict access to University of Pittsburgh for a period of 1 year.
Number of Pages: 68
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Electrical and Computer Engineering
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Optical Computing, Coherent Photo-electric Processing, Time-Multiplexed Architecture
Date Deposited: 11 Jan 2024 19:43
Last Modified: 11 Jan 2024 19:43


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