3 papers
cs.AR2025
Weight Transformations in Bit-Sliced Crossbar Arrays for Fault Tolerant Computing-in-Memory: Design Techniques and Evaluation Framework
Akul Malhotra, Sumeet Kumar Gupta
The deployment of deep neural networks (DNNs) on compute-in-memory (CiM) accelerators offers significant energy savings and speed-up by reducing data movement during inference. How…
cs.AR2025
ReTern: Exploiting Natural Redundancy and Sign Transformations for Enhanced Fault Tolerance in Compute-in-Memory based Ternary LLMs
Akul Malhotra, Sumeet Kumar Gupta
Ternary large language models (LLMs), which utilize ternary precision weights and 8-bit activations, have demonstrated competitive performance while significantly reducing the high…
cs.AR2024
BinSparX: Sparsified Binary Neural Networks for Reduced Hardware Non-Idealities in Xbar Arrays
Akul Malhotra, Sumeet Kumar Gupta
Compute-in-memory (CiM)-based binary neural network (CiM-BNN) accelerators marry the benefits of CiM and ultra-low precision quantization, making them highly suitable for edge comp…