75 citations · 206 across the 28 of their papers we have counts for
4 papers · 1 filter
Approximate Computing and the Efficient Machine Learning Expedition
Jörg Henkel, Hai Li, Anand Raghunathan +4
Approximate computing (AxC) has been long accepted as a design alternative for efficient system implementation at the cost of relaxed accuracy requirements. Despite the AxC researc…
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…