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The opinions, findings, and conclusions or recommendations expressed are those of the Center author(s) and do not necessarily reflect the views of the National Science Foundation.

Center Overview

Emerging applications involving large-scale data and high-complexity computational models are challenging existing computing resources. CHMPR and its affiliated industry and government partners aim to be the preeminent cooperative research consortium for addressing the productivity, performance, and scalability issues that lie at the heart of these challenges. CHMPR research draws on the diverse computational science expertise available at the partnering universities to address industry’s current and future multicore application needs through the continual improvement of multicore architectures and open source tools.

CHMPR’s vision is to become a leading national center in providing service-oriented computational solutions. These solutions employ multicore technologies for the optimization of problems in the fields of environmental and geophysical sciences, chemical, aerospace, defense, biomedical informatics, financial, and event-driven simulations and visualizations.

Universities

  • Rutgers University, Newark
  • North Carolina State University
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Center Personnel

Dr. Gregg Rothermel
Site Director, NC State University

Rada Chirkova

9195152444
chirkova@csc.ncsu.edu

Vijayalakshmi Atluri

9739720283
atluri@rutgers.edu

Research Focus

The specific multicore applications and cloud computing services will be focused on:

  • Big Data computations: personal medical intelligence, climate change, bio-cellular imaging, materials genomics.
  • Sustainable environment: human sensor networks, visual animation social media mining and modeling.
  • Next-gen computing platforms, including: GPU/CPU hybrid workflow systems, 512 node IBM iDataplex Dual Intel Nehalem processors, peta-exascale storage systems, and quantum computing.
  • Cognitive and neuroscience: hybrid compute hardware and software designs for previously incomputable domains of social consequence.
  • Assured social media information: crowd sourcing, false information, steganography detection.

As part of this, CHMPR will conduct:

  • Performance analysis and scaling optimization of data-intensive modeling and simulation applications on hybrid multicore systems.
  • Software tool deployments and algorithmic design to take advantage of parallel distributed computing.
  • Interactive digital media and 3D graphic environments.

Awards