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Study of the Utilization of Adaptive Computing in Space Applications

Study of the Utilization of Adaptive Computing in Space Applications. Marco Figueiredo ASDP - Adaptive Scientific Data Processing Group website: http://fpga.gsfc.nasa.gov. Microelectronics and Signal Processing Branch - Code 564 Goddard Space Flight Center. Introduction to the ASDP Group.

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Study of the Utilization of Adaptive Computing in Space Applications

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  1. Study of the Utilization of Adaptive Computing in Space Applications Marco Figueiredo ASDP - Adaptive Scientific Data Processing Group website: http://fpga.gsfc.nasa.gov Microelectronics and Signal Processing Branch - Code 564 Goddard Space Flight Center

  2. Introduction to the ASDP Group • ASDP Group • Marco Figueiredo (SGT, Inc.) • Umesh Patel (SGT, Inc.) • Ken Winiecki (Lockheed Martin Corp.) • Terry Graessle (Lockheed Martin Corp.) • Parminder Ghuman (GSFC) • Mission: Foster adaptive computing technology evolution by applying it to remote sensing science applications and providing feedback to industry & academia MAPLD 98

  3. Overview • The Earth science remote sensing data flow • The MODIS reflective calibration prototype • The adaptive computing application design process • Improvements needed for the cost-effective development of adaptive computing applications • Conclusions MAPLD 98

  4. Earth Science Remote SensingData Flow Diagram MAPLD 98

  5. MODIS Reflective Calibration Algorithm 9.28 times acceleration MAPLD 98

  6. Application Design Approach • Analyze the algorithm and identify computation intensive parts that can benefit from execution on an adaptive processor. • Algorithm Partitioning and Mapping • Incremental Design, Test, and Integration MAPLD 98

  7. Application DesingAlgorithm Partitioning and Mapping • Extract data flow diagram and partition tasks between host and adaptive processor • Perform a fixed point precision analysis and determine data path width • Create a detailed hardware data flow diagram • Perform FPGA resource estimation • Perform design mapping to adaptive processor MAPLD 98

  8. Wildforce Adaptive Processor

  9. Mapping Issues • Amount of logic that would fit into each device • Amount of data to be passed between FPGAs • How input parameters would be made available to each FPGA • How the data would flow in and out of the board

  10. Incremental Design, Test, and Integration • Design a small portion of the logic in VHDL and simulate the design • Synthesize, place and route the FPGA design • Write host software to download and test the design to the board comparing results with fixed-point simulation • Repeat steps 1 to 3 until design is complete • Allows the division of taks among engineers • Reduces compilation time and facilitates test MAPLD 98

  11. Application DevelopmentRequired Skills • Algorithm analysis • Complex logic design (arithmetic) • VHDL design • FPGA design • Reconfigurable computer architectures • Software engineering MAPLD 98

  12. Improvements Needed • Extended library of high performance math operators for specific device architectures • Transparent design environment that crosses the microprocessor (software) and fpga (hardware) boundaries • JAVA • VHDL MAPLD 98

  13. Improvements Needed (cont.) • High level design entry tool for: • Algorithm capturing • Fixed point precision analysis • Host/Adaptive processor design partitioning • Adaptive processor mapping tool • Design documentation • Adaptive Computer Engineers MAPLD 98

  14. Conclusions • Adaptive (reconfigurable) computing yields orders of magnitude acceleration over microprocessor based systems TODAY. • The utilization of a spacecraft adaptive computer presents the same potentials and limitations found on ground applications. Development cost Number of applications MAPLD 98

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