75 citations · 206 across the 28 of their papers we have counts for
7 papers · 1 filter
A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks
Wilfried Haensch, Anand Raghunathan, Kaushik Roy +4
Deep Learning neural networks are pervasive, but traditional computer architectures are reaching the limits of being able to efficiently execute them for the large workloads of tod…
Piezoelectric Strain FET (PeFET) based Non-Volatile Memories
Niharika Thakuria, Reena Elangovan, Anand Raghunathan +1
We propose non-volatile memory (NVM) designs based on Piezoelectric Strain FET (PeFET) utilizing a piezoelectric/ferroelectric (PE/FE such as PZT) coupled with 2D Transition Metal…
STeP-CiM: Strain-enabled Ternary Precision Computation-in-Memory based on Non-Volatile 2D Piezoelectric Transistors
Niharika Thakuria, Reena Elangovan, Sandeep K Thirumala +2
We propose 2D Piezoelectric FET (PeFET) based compute-enabled non-volatile memory for ternary deep neural networks (DNNs). PeFETs consist of a material with ferroelectric and piezo…
Valley-Coupled-Spintronic Non-Volatile Memories with Compute-In-Memory Support
Sandeep Thirumala, Yi-Tse Hung, Shubham Jain +6
In this work, we propose valley-coupled spin-hall memories (VSH-MRAMs) based on monolayer WSe2. The key features of the proposed memories are (a) the ability to switch magnets with…
RxNN: A Framework for Evaluating Deep Neural Networks on Resistive Crossbars
Shubham Jain, Abhronil Sengupta, Kaushik Roy +1
Resistive crossbars designed with non-volatile memory devices have emerged as promising building blocks for Deep Neural Network (DNN) hardware, due to their ability to compactly an…
Computing in Memory with Spin-Transfer Torque Magnetic RAM
Shubham Jain, Ashish Ranjan, Kaushik Roy +1
In-memory computing is a promising approach to addressing the processor-memory data transfer bottleneck in computing systems. We propose Spin-Transfer Torque Compute-in-Memory (STT…
STT-SNN: A Spin-Transfer-Torque Based Soft-Limiting Non-Linear Neuron for Low-Power Artificial Neural Networks
Deliang Fan, Yong Shim, Anand Raghunathan +1
Recent years have witnessed growing interest in the use of Artificial Neural Networks (ANNs) for vision, classification, and inference problems. An artificial neuron sums N weighte…