2 papers
cs.AR2026
A Reconfigurable Multiplier Architecture for Error-Resilient Applications in RISC-V Core
Pragun Jaswal, L. Hemanth Krishna, B. Srinivasu
Neural Networks (NNs) have been widely adopted due to their outstanding efficacy and adaptability across computer vision and deep learning applications. The optimization of NNs is…
cs.AR2025
Low Power Approximate Multiplier Architecture for Deep Neural Networks
Pragun Jaswal, L. Hemanth Krishna, B. Srinivasu
This paper proposes an low power approximate multiplier architecture for deep neural network (DNN) applications. A 4:2 compressor, introducing only a single combination error, is d…