699 citations · 816 across the 5 of their papers we have counts for
5 papers
NWChem: Past, Present, and Future
E. Aprà, E. J. Bylaska, W. A. de Jong +111
Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts…
GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent
Jeff Daily, Abhinav Vishnu, Charles Siegel +2
In this paper, we present GossipGraD - a gossip communication protocol based Stochastic Gradient Descent (SGD) algorithm for scaling Deep Learning (DL) algorithms on large-scale sy…
What does fault tolerant Deep Learning need from MPI?
Vinay Amatya, Abhinav Vishnu, Charles Siegel +1
Deep Learning (DL) algorithms have become the de facto Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive - even distributed…
User-transparent Distributed TensorFlow
Abhinav Vishnu, Joseph Manzano, Charles Siegel +1
Deep Learning (DL) algorithms have become the {\em de facto} choice for data analysis. Several DL implementations -- primarily limited to a single compute node -- such as Caffe, Te…
Distributed TensorFlow with MPI
Abhinav Vishnu, Charles Siegel, Jeffrey Daily
Machine Learning and Data Mining (MLDM) algorithms are becoming increasingly important in analyzing large volume of data generated by simulations, experiments and mobile devices. W…