66 citations · 68 across the 3 of their papers we have counts for
4 papers
Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks
Dharma Teja Vooturi, Girish Varma, Kishore Kothapalli
Sparse neural networks are shown to give accurate predictions competitive to denser versions, while also minimizing the number of arithmetic operations performed. However current h…
A Study of BFLOAT16 for Deep Learning Training
Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi +16
This paper presents the first comprehensive empirical study demonstrating the efficacy of the Brain Floating Point (BFLOAT16) half-precision format for Deep Learning training acros…
Hierarchical Block Sparse Neural Networks
Dharma Teja Vooturi, Dheevatsa Mudigere, Sasikanth Avancha
Sparse deep neural networks(DNNs) are efficient in both memory and compute when compared to dense DNNs. But due to irregularity in computation of sparse DNNs, their efficiencies ar…
Efficient Inferencing of Compressed Deep Neural Networks
Dharma Teja Vooturi, Saurabh Goyal, Anamitra R. Choudhury +2
Large number of weights in deep neural networks makes the models difficult to be deployed in low memory environments such as, mobile phones, IOT edge devices as well as "inferencin…