Browsing Department of Computational and Data Sciences (CDS) by Subject "Distributed Computing"
Now showing items 1-2 of 2
-
Abstractions and Optimizations for Data-driven Applications Across Edge and Cloud
Modern data driven applications have a novel set of requirements. Advances in deep neural networks (DNN) and computer vision (CV) algorithms have made it feasible to extract meaningful insights from large-scale deployments ... -
Efficient betweenness Centrality Computations on Hybrid CPU-GPU Systems
(2017-10-11)Analysis of networks is quite interesting, because they can be interpreted for several purposes. Various features require different metrics to measure and interpret them. Measuring the relative importance of each vertex ...