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High-performance Computing & Simulation Research Lab
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Advanced Space Computing: Design and Analysis of Architectures, Networks, Systems, and Applications for Advanced Space and Aerospace Platforms

The advanced space computing (ASC) group focuses on a broad variety of research challenges in computer engineering for systems and applications on space and aerospace platforms. Research, development, and analysis are undertaken using both simulative and experimental methods toward high-performance embedded computing in the limited design space for mission-critical space and airborne platforms.

Space-based radar (SBR), multi-spectral imaging, and many other high-performance applications are creating orders of magnitude more data than the limited-bandwidth downlinks on space and aerospace platforms can support. As such, mission planners are demanding advanced computing with more onboard payload processing to improve autonomous operations and reduce the amount of data sent over downlinks. Future platforms will also need to be inexpensive, flexible, scalable, and able to support reduced development schedules while saving size, weight, power, etc. Meanwhile, with the need to meet these rigorous requirements, there is an ever-increasing push to use COTS technologies to develop general- and multi-purpose payloads in a cost-effective manner. This set of issues forms the basic framework for the activities of the ASC group.

The ASC team is currently active on two projects, one on research and development toward the first supercomputer in space for NASA (NMP) and the other on flexible, reconfigurable interconnects for space systems (RIO).

Sponsor: NASA, Honeywell
Principal Investigator: Dr. Alan D. George

Group Members
Greg Cieslewski, PhD student, group co-leader
Chris Conger, PhD student
Eric Grobelny, PhD candidate, Alumni Fellow
Adam Jacobs, PhD student, Alumni Fellow, group co-leader
John Wernsing, PhD student

Related Links

  • IEEE Aerospace Conference
  • High-Performance Embedded Computing (HPEC) Workshop

    Acknowledgements
    We gratefully acknowledge the following vendor for their support of the projects in this group:

  • MLDesign Technologies for their donation of software tools.