25 citations · 50 across the 6 of their papers we have counts for
5 papers · 1 filter
NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems
Shubham Negi, Indranil Chakraborty, Aayush Ankit +1
In-Memory Computing (IMC) hardware using Memristive Crossbar Arrays (MCAs) are gaining popularity to accelerate Deep Neural Networks (DNNs) since it alleviates the "memory wall" pr…
GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural Networks
Indranil Chakraborty, Mustafa Fayez Ali, Dong Eun Kim +2
The analog nature of computing in Memristive crossbars poses significant issues due to various non-idealities such as: parasitic resistances, non-linear I-V characteristics of the…
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti +8
Memristor crossbars are circuits capable of performing analog matrix-vector multiplications, overcoming the fundamental energy efficiency limitations of digital logic. They have be…
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays
Amogh Agrawal, Akhilesh Jaiswal, Deboleena Roy +4
Deep neural networks are a biologically-inspired class of algorithms that have recently demonstrated state-of-the-art accuracies involving large-scale classification and recognitio…
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks
Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda +1
Neuromorphic computing using post-CMOS technologies is gaining immense popularity due to its promising abilities to address the memory and power bottlenecks in von-Neumann computin…