3 citations · 7 across the 17 of their papers we have counts for
21 papers
HippocamPEX: A Hippocampus-Inspired In-Silico Architecture for Context-Aware Sequence Prediction
Md Abdullah al Kaiser, Keiland W. Cooper, Rouhan Noor +9
The brain's hippocampus enables episodic memory - the ability to encode events within their context, organize them into sequences, and generate predictive representations to guide…
HippocamFLEX: FPGA Prototyping of Hippocampus-Inspired Architecture for Context-Aware Sequence Prediction
Bhuvanesh S. Kayarabettu, Hamed Poursiami, Keiland Cooper +4
Unlike conventional architectures that treat memory as static pattern storage, the hippocampus organizes experience as ordered sequences and retrieves them through temporally compr…
Calibration-Free Photonic Memory in a Silicon Photonics Platform
Ankur Singh, Akhilesh Jaiswal
We propose a calibration-free photonic memory bitcell based on nonresonant variable optical attenuators in the GlobalFoundries 45SPCLO platform. The cell maintains complementary el…
A Voltage-controlled MTJ-CMOS Neuron Emulating Tunable Izhikevich-Inspired Dynamics
Kayode Oluwaseyi Adebunmi, Jordan Athas, Allison Fleming +5
Biological neurons exhibit diverse firing dynamics that enable adaptive and stimulus-dependent signalling, yet reproducing these dynamics in hardware has remained an enduring chall…
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…
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…
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…
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…
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…
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…
X-pSRAM: A Photonic SRAM with Embedded XOR Logic for Ultra-Fast In-Memory Computing
Md Abdullah-Al Kaiser, Sugeet Sunder, Ajey P. Jacob +1
Traditional von Neumann architectures suffer from fundamental bottlenecks due to continuous data movement between memory and processing units, a challenge that worsens with technol…
A Mixed-Signal Photonic SRAM-based High-Speed Energy-Efficient Photonic Tensor Core with Novel Electro-Optic ADC
Md Abdullah-Al Kaiser, Sugeet Sunder, Ajey P. Jacob +1
The rapid surge in data generated by Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) applications demands ultra-fast, scalable, and energy-efficie…
A Retina-Inspired Pathway to Real-Time Motion Prediction inside Image Sensors for Extreme-Edge Intelligence
Subhradip Chakraborty, Shay Snyder, Md Abdullah-Al Kaiser +3
The ability to predict motion in real time is fundamental to many maneuvering activities in animals, particularly those critical for survival, such as attack and escape responses.…
Design of Energy-Efficient Cross-coupled Differential Photonic-SRAM (pSRAM) Bitcell for High-Speed On-Chip Photonic Memory and Compute Systems
Md Abdullah-Al Kaiser, Sugeet Sunder, Clynn Mathew +3
In this work, we propose a novel differential photonic static random access memory (pSRAM) bitcell design using fabrication-friendly photonic components. The proposed pSRAM overcom…
Predictive Performance of Photonic SRAM-based In-Memory Computing for Tensor Decomposition
Sasindu Wijeratne, Sugeet Sunder, Md Abdullah-Al Kaiser +4
Photonics-based in-memory computing systems have demonstrated a significant speedup over traditional transistor-based systems because of their ultra-fast operating frequencies and…
A Pathway to Near Tissue Computing through Processing-in-CTIA Pixels for Biomedical Applications
Zihan Yin, Subhradip Chakraborty, Ankur Singh +3
Near-tissue computing requires sensor-level processing of high-resolution images, essential for real-time biomedical diagnostics and surgical guidance. To address this need, we int…
Voltage-Controlled Magnetic Tunnel Junction based ADC-less Global Shutter Processing-in-Pixel for Extreme-Edge Intelligence
Md Abdullah-Al Kaiser, Gourav Datta, Jordan Athas +5
The vast amount of data generated by camera sensors has prompted the exploration of energy-efficient processing solutions for deploying computer vision tasks on edge devices. Among…
Energy-Efficient & Real-Time Computer Vision with Intelligent Skipping via Reconfigurable CMOS Image Sensors
Md Abdullah-Al Kaiser, Sreetama Sarkar, Peter A. Beerel +2
Current video-based computer vision (CV) applications typically suffer from high energy consumption due to reading and processing all pixels in a frame, regardless of their signifi…
Retina-Inspired Object Motion Segmentation for Event-Cameras
Victoria Clerico, Shay Snyder, Arya Lohia +4
Event-cameras have emerged as a revolutionary technology with a high temporal resolution that far surpasses standard active pixel cameras. This technology draws biological inspirat…
Hardware-Algorithm Re-engineering of Retinal Circuit for Intelligent Object Motion Segmentation
Jason Sinaga, Victoria Clerico, Md Abdullah-Al Kaiser +5
Recent advances in retinal neuroscience have fueled various hardware and algorithmic efforts to develop retina-inspired solutions for computer vision tasks. In this work, we focus…
Toward High Performance, Programmable Extreme-Edge Intelligence for Neuromorphic Vision Sensors utilizing Magnetic Domain Wall Motion-based MTJ
Md Abdullah-Al Kaiser, Gourav Datta, Peter A. Beerel +1
The desire to empower resource-limited edge devices with computer vision (CV) must overcome the high energy consumption of collecting and processing vast sensory data. To address t…