22 citations · 40 across the 21 of their papers we have counts for
3 papers · 1 filter
Flex-PE: Flexible and SIMD Multi-Precision Processing Element for AI Workloads
Mukul Lokhande, Gopal Raut, Santosh Kumar Vishvakarma
The rapid adaptation of data driven AI models, such as deep learning inference, training, Vision Transformers (ViTs), and other HPC applications, drives a strong need for runtime p…
HYDRA: Hybrid Data Multiplexing and Run-time Layer Configurable DNN Accelerator
Sonu Kumar, Komal Gupta, Gopal Raut +2
Deep neural networks (DNNs) offer plenty of challenges in executing efficient computation at edge nodes, primarily due to the huge hardware resource demands. The article proposes H…
HOAA: Hybrid Overestimating Approximate Adder for Enhanced Performance Processing Engine
Omkar Kokane, Prabhat Sati, Mukul Lokhande +1
This paper presents the Hybrid Overestimating Approximate Adder designed to enhance the performance in processing engines, specifically focused on edge AI applications. A novel Plu…