ASPIRE: GPU Computing Testbed Platform for Research and Education of Advanced Persistent Threats and learn to Reason in Adversarial Environments
Abstract
The goal of this DURIP proposal is to build a GPU based compact supercomputer testbed called ASPIRE that would support the ongoing ONR MURI research on advanced persistent threats, with project name ADAPT, that is led by the University of Washington Team. ADAPT is a data-driven MURI project that aims to model the interactions between the adversary and the systems. The detailed system model and the interaction logs are created by MURI team members from Georgia Tech. The data volume is quite large requiring computational capabilities that would be supporting the efforts. In addition, the UW team has been investigating adversarial machine learning in real application data sets such as images and videos. Each of these data sets typically require several days of computations on regular CPU machines. The GPU based systems are built with such data intensive machine learning applications in mind and are well suited to handle needed computations. In addition, the testbed ASPIRE would also support related educational components at UW EE and has the capability to provide support at the College of Engineering at undergraduate, graduate, and professional masters level courses. As outlined in the proposal we will be able to develop one undergraduate course, two graduate courses, and significantly enhance the ENGINE program, which is a very successful, yearlong, senior capstone design sequence at UW EE. The ASPIRE testbed will thus be a transformative addition to both research and educational activities at the UW.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 10, 2018
- Source ID
- N000141812250
Entities
People
- Linda Bushnell
Organizations
- Office of Naval Research
- United States Navy
- University of Washington