SpaceCubeX

Overview

On-board Computing Analysis Framework

Enables simulation and emulation of heterogeneous on-board
processing architectures

High Productivity Tools

Mapping python applications to FPGA-based systems

Heterogeneous SpaceCube Hardware

Hardware prototyping of next generation flight hardware

 
 
 

This project builds upon prior efforts, which developed a framework for automated trade space exploration of on-board heterogeneous computing solutions, to address emerging distributed measurement and multi-satellite NASA Earth Science missions. These missions invoke requirements for distributed sensing, data continuity, satellite constellation station keeping, and intelligent sensor control, which would require an estimated 10-110x increase in onboard computing requirements. Distributed sensing missions require application portability across platform types; however, platform constraints lead UAVs and satellites to utilize different co-processor accelerators (GPUs vs. FPGAs). A common framework that supports both FPGAs and GPUs will facilitate migration between these platform types. Multi-satellite missions enable diurnal and multi-angle measurements, and invoke complex communication and control logic that must be processed on-board. Intelligent sensor control capabilities present complex, ad hoc processing, requiring experimentation on prototype hardware.

The SpaceCubeX project addresses these challenges by extending the evolvable testbed to include GPU support, model distributed sensors and high bandwidth communication links, develop prototype hardware, and demonstrate the technology. The University of Southern California`s Information Sciences Institute (USC/ISI) will oversee the effort, leading the extension of the framework. NASA Goddard Space Flight Center will develop a prototype science mission processor and provide multi-satellite applications. NASA Ames Research Center will provide distributed sensing applications (FluidCam, MiDAR)

The material is based upon work supported by NASA under award No(s) 80NSSC17K0286 and NNX15AH32G. 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 Aeronautics and Space Administration. This work is also supported by generous donations from Amazon AWS and Xilinx.

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