activity
20192026
most citedTowards Low-Latency Energy-Efficient Deep SNNs via Attention-Guided Compression

12 citations · 32 across the 25 of their papers we have counts for

collaborators
Showing cs.ARShow all

6 papers · 1 filter

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…

cs.AR2026

In-Memory ADC-Based Nonlinear Activation Quantization for Efficient In-Memory Computing

Shuai Dong, Junyi Yang, Biyan Zhou +3

In deep networks, operations such as ReLU and hardware-driven clamping often cause activations to accumulate near the edges of the distribution, leading to biased clustering and su…

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…

cs.AR2024

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…

cs.AR2024

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…

cs.AR2020

qBSA: Logic Design of a 32-bit Block-Skewed RSFQ Arithmetic Logic Unit

Souvik Kundu, Gourav datta, Peter A. Beerel +1

Single flux quantum (SFQ) circuits are an attractive beyond-CMOS technology because they promise two orders of magnitude lower power at clock frequencies exceeding 25 GHz.However,…