Los Alamos National LaboratoryInformation Science and Technology Institute (ISTI)
Implementing and fostering collaborative research, workforce and program development, and technical exchange

Cloud Computing 2018

ISTI solicits Rapid Response Research Proposals on the topic of Cloud Computing in Amazon Web Services.


  • Institute Director
  • Jim Ahrens
  • (505) 667-5797
  • Email
  • Professional Staff Assistant
  • Veronica Rodriguez
  • (505) 665-0528
  • Email

May 2018

Rapid Response Research Call for Proposals
Submission deadline is June 15, 2018.

September 19, 2018, 1:30 – 5 pm

Rapid Response Familiarization Cloud Computing Talks/Demos

Location: Oppenheimer Study Center, Jemez/Cochiti Rooms
Final Report (pdf)

Computational Physics Applications
  • Accelerating Hydrodynamics and Turbulence Modeling with Efficient Deep Learning on Amazon AWS GPUs, A. Mohan (T-4/CNLS)
  • An Autonomous Security System with AWS DeepLens, C. Kiss (A-2)
  • DOE Climate Models for Risk Assessment on the Cloud, D. Pasqualini (A-1)
  • Enabling Wildland Fire Managers to Explore the Fire Response Space, M. Holmes (EES-16)
  • Mapping Industrial Seismic Noise in the Continental US, J. MacCarthy (EES-17)
  • Framework for On-Demand Cloud Computation of Theoretical Models of Materials over Discretized Phase Volumes, D. Fobes (A-1)
Data Science Applications and Logistics
  • Enterprise Scaling of Co-Evolving Attacker and Defender Strategies for Large Infrastructure Networks (CEADS-LIN), E. Michalak (A-4)
  • Evaluating a C++ Distributed Big Data Analytics Framework for HPC and Cloud Platforms, L. Li-Ta (CCS-7)
  • VR/AR Applications (Virtual Reality), D. Heimer (NEN-3)
  • Migration of Unclassified Amazon to Amazon Secure Cloud (C2S), Z. Baker (CCS-7)
  • Smart Machine-Learning Workflows in the Cloud, J. Ambrosiano (A-1)
Machine Learning Applications
  • RF Modulation Classification, A. Skurikhin (ISR-3)
  • SASSY-CLOUD: Scalable Architecture for Serious Signal analysis in the Cloud, R. Porter (CCS-3)
  • Exploring Cloud Computing for Collection and Analysis of Image Data, D. Oyen (CCS-3)
  • Deep Learning Image Segmentation on Cloud Computing, P. Romero (HPC-ENV)
  • Cloud-based Image Analysis, Z. Wang (P-25)