DURIP: Building a GPU Computational Infrastructure Platform for Heterogeneous Big Data Analysis and Understanding

Abstract

In this proposed effort, we plan on building a powerful and flexible GPU computational infrastructure platform which consists of (i) a GPU cluster with more than 79,000 GPU cores and around 80 CPU cores including three requested cutting-edge GPU supercomputers and ten existing desktops, and (ii) a mobile base with on-board computer for robots. The platform will be used by both the Vision, Information, and Statistical Signal Theories and Applications (VISSTA) lab directed by the co-Pl Krim, and the Interpretable Visual Modeling and Computing Lab (iVMCL) currently created by the PI Wu in the department of Electrical and Computer Engineering at NC State University (NCSU). The proposed computational platform will enable the two to address ongoing research projects on heterogeneous Big Data analysis and deep understanding, as well as to smoothly prepare for future ones. This new platform will complement and match the input modalities already present at the two labs, and expand current capabilities in aggregating, parsing, fusing and ultimately analyzing and understanding heterogeneous Big Data in the following applications relevant to the Department of Defense (DoD): (i) Sensor Networks of various modalities (static or mobile) such as deep understanding of scene and events of a camera network; (ii) Social Networks with information stored locally, and (iii) Bioinformatics data, specifically related to the brain connectome, both based on topological data analysis theory; (iv) Robot autonomy by learning from situated dialogue (i.e., verbal instructions grounded on visual demonstration) and physiological sensing. Not only will the proposed GPU cluster enable PI Wu and co-PI Krim to investigate and pursue a genuine parallel implementation of many already successful centralized models and algorithms, but also be beneficial to students (undergraduates and graduates) in the classes regularly taught by PI Wu and co-Pl Krim, as well as other research groups at NCSU since the proposed cluster will be seamlessly integrated, and bring new feature, into the university s computing platform.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 14, 2019
Source ID
W911NF1810209

Entities

People

  • Tianfu Wu

Organizations

  • Army Contracting Command
  • North Carolina State University
  • United States Army

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • Autonomy