28 citations · 40 across the 4 of their papers we have counts for
9 papers
Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization
Lipeng Wan, Axel Huebl, Junmin Gu +12
The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity…
Analyzing scientific data sharing patterns for in-network data caching
Elizabeth Copps, Huiyi Zhang, Alex Sim +6
The volume of data moving through a network increases with new scientific experiments and simulations. Network bandwidth requirements also increase proportionally to deliver data w…
Improving Botnet Detection with Recurrent Neural Network and Transfer Learning
Jeeyung Kim, Alex Sim, Jinoh Kim +2
Botnet detection is a critical step in stopping the spread of botnets and preventing malicious activities. However, reliable detection is still a challenging task, due to a wide va…
Deep Learning on Real Geophysical Data: A Case Study for Distributed Acoustic Sensing Research
Vincent Dumont, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin +1
Deep Learning approaches for real, large, and complex scientific data sets can be very challenging to design. In this work, we present a complete search for a finely-tuned and effi…
Botnet Detection Using Recurrent Variational Autoencoder
Jeeyung Kim, Alex Sim, Jinoh Kim +1
Botnets are increasingly used by malicious actors, creating increasing threat to a large number of internet users. To address this growing danger, we propose to study methods to de…
IDEALEM: Statistical Similarity Based Data Reduction
Dongeun Lee, Alex Sim, Jaesik Choi +1
Many applications such as scientific simulation, sensing, and power grid monitoring tend to generate massive amounts of data, which should be compressed first prior to storage and…