SpaceCubeX: On-board processing for Distributed Measurement and Multi-Satellite Missions

This proposal addresses NASA's Earth Science missions and its underlying needs for high performance, scalable on-board processing. The decadal survey missions stressed higher resolution instruments and persistent measurements, which drove computing needs up by 100-1,000x. Our AIST-14 SpaceCubeX effort developed a framework which supported rapid trade space exploration of on-board heterogeneous computing solutions (Multi-core CPUs coupled with DSP or FPGA co-processors) across a benchmark suite of Earth Science applications, achieving 20-20,000x performance improvements. Today, measurement capabilities emerging from the upcoming 2017 decadal survey such as distributed sensing, data continuity, multi-satellite constellations, and intelligent sensor control will require an additional 10-100x increase in onboard computing performance. For this renewal effort, we propose to extend the SpaceCubeX on-board compute analysis framework and develop a hardware prototype to support the evaluation of these new measurement criteria. Distributed sensing missions require application portability across platform types, however platform constraints lead UAVs and satellites to utilize different processor types (GPUS vs FPGAs). A common framework which 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 which must be processed on-board. Intelligent sensor control capabilities present complex, ad hoc processing which requires 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. SpaceCubeX provides the following benefits: -Accessible, rapid prototyping of next generation satellite and multi-satellite constellations capabilities by creating virtual satellites in the cloud. -A proto-type heterogeneous on-board computer for experimentation of advanced autonomy and control capabilities required by intelligent instrument control and constellation management. -Accelerate migration of missions from UAV and airborne platforms to satellites to support distributed sensing. -Accurate, scalable approach to assessing Multi-Satellite mission performance. -Detailed analysis and initial run-time implementation of FluidCam Structure from Motion, MiDAR, Diurnal Measurements, and Mult-Angle Measurement applications. This project utilizes advanced instruments (FluidCam and MiDAR) currently operational on UAV platforms to drive distributed sensing and intelligent sensor research, and upcoming sensing concepts (Diurnal Measurements and Multi-angle Measurements) to guide multi-satellite constellation platform research. SpaceCubeX leverages substantial research investments from NASA, DARPA, and NRO on revolutionary imaging instruments, space based computing, multi-core and FPGA architectures, and focuses them on NASA Earth science missions and applications. The core team has worked together successfully for 14 years. 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. NASA Jet Propulsion Laboratory will advise on application mapping to heterogeneous processors. The team will perform in these areas over a two year period to develop a distributed sensing and multi-satellite framework capabilities in year 1 and to use this framework to characterize end to end performance of candidate processor architectures and create a hardware prototype in year 2, raising the TRL from 3 to 5 in all areas.

Advance Earth system science knowledge through the identification, development, and demonstration of innovative information systems technologies

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