RAPTOR
Reconfigurable Advanced Platform for Transdisciplinary Open Research
About Raptor
Building resilient, sustainable, livable, and environmentally safe dynamic systems (natural or human built) requires on-demand computing resources, facilitating machine learning, data processing, and data analytics. These systems rely on computation to support simulation, modeling, and analyses to enable discovery, facilitate understanding, and make decisions. This project implements RAPTOR (Reconfigurable Advanced Platform for Transdisciplinary Open Research), a reconfigurable compute environment to address dynamic and diverse computing needs of science drivers––coastal resilience, sustainable environmental research, and systems biology.
Featured Applications
Recent News
Fellowships
RAPTOR at PearC 22 | Student Experience – Carolina Martinez
Overall Experience at PearC22 Conference: Before being accepted into the CAESCIR fellowship, I had...
NSF REU Reconfigurable Advanced Platform for Transdisciplinary Open Research (RAPTOR) Student Fellowships
The Knight Foundation School of Computing and Information Sciences and the Division of Information...
Recent News
RAPTOR at PearC 22 | Student Experience – Carolina Martinez
Overall Experience at PearC22 Conference: Before being accepted into the CAESCIR fellowship, I had...
NIH awards FIU $1M to develop machine-learning algorithms to study proteins – important for understanding, treating diseases
The National Institutes of Health (NIH) has awarded FIU researchers a $1 million grant to design...
RAPTOR at PearC 22 | Student Experience – Carolina Martinez
Overall Experience at PearC22 Conference: Before being accepted into the CAESCIR fellowship, I had...
Fellowships
NSF REU Reconfigurable Advanced Platform for Transdisciplinary Open Research (RAPTOR) Student Fellowships
The Knight Foundation School of Computing and Information Sciences and the Division of Information...
This material is based upon work supported by the National Science Foundation under Grant No. 2126253. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.