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20242026
most citedSystem-Level Performance Modeling of Photonic In-Memory Computing

1 citations · 1 across the 12 of their papers we have counts for

collaborators

17 papers

cs.AR2026

A Time-Encoded Analog Photonic Interposer for Energy-EfficientIntegration of Analog Vision Sensors and Analog Accelerators

Subhradip Chakraborty, Zihan Yin, Xuming Chen +3

This work introduces a time-encoded analog photonic interposer that enables long-distance, high-fidelity transport of analog signals between spatially separated chiplets. Unlike pr…

physics.optics2026

OptiLookUp: An Optical ROM-Based Lookup Table Engine for Photonic Accelerators

Ankur Singh, Akhilesh Jaiswal

Read-only memory (ROM) provides deterministic access to predefined data mappings. Extending ROM concepts to the optical domain enables high-bandwidth, low-latency, and parallel mem…

cs.AR2026

GEM3D CIM General Purpose Matrix Computation Using 3D Integrated SRAM eDRAM Hybrid Compute In Memory on Memory Architecture

Subhradip Chakraborty, Ankur Singh, Akhilesh R. Jaiswal

With the rapid growth of deep neural networks (DNNs), compute-in-memory (CIM) has emerged as a promising energy-efficient paradigm for accelerating multiply-and-accumulate (MAC) op…

stat.ML2026

ConformalHDC: Uncertainty-Aware Hyperdimensional Computing with Application to Neural Decoding

Ziyi Liang, Hamed Poursiami, Zhishun Yang +5

Hyperdimensional Computing (HDC) offers a computationally efficient paradigm for neuromorphic learning. Yet, it lacks rigorous uncertainty quantification, leading to open decision…

cs.DC20261 cited

System-Level Performance Modeling of Photonic In-Memory Computing

Jebacyril Arockiaraj, Sasindu Wijeratne, Sugeet Sunder +4

Photonic in-memory computing is a high-speed, low-energy alternative to traditional transistor-based digital computing that utilizes high photonic operating frequencies and bandwid…

cs.AR2025

NVM-in-Cache: Repurposing Commodity 6T SRAM Cache into NVM Analog Processing-in-Memory Engine using a Novel Compute-on-Powerline Scheme

Subhradip Chakraborty, Ankur Singh, Xuming Chen +2

The rapid growth of deep neural network (DNN) workloads has significantly increased the demand for large-capacity on-chip SRAM in machine learning (ML) applications, with SRAM arra…