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    • Home
    • Project
      • Project Vision
      • ASAP Impact
      • Partners
      • WP Overview
      • WP1: Management
      • WP2: Algorithms Selection
      • WP3: Testbed hardware
      • WP4: Testbed software
      • WP5: Flight Simulator
      • WP6: Dissemination
    • Publications
    • EEAB
    • News
      • Newsletters
      • Events
    • Github
    • Contact
  • Home
  • Project
    • Project Vision
    • ASAP Impact
    • Partners
    • WP Overview
    • WP1: Management
    • WP2: Algorithms Selection
    • WP3: Testbed hardware
    • WP4: Testbed software
    • WP5: Flight Simulator
    • WP6: Dissemination
  • Publications
  • EEAB
  • News
    • Newsletters
    • Events
  • Github
  • Contact

WP4: Testbed Software Interface and Validation Tests

WP4 focuses on developing a software framework to port machine learning (ML) models onto FPGA prototypes created in WP3. This includes creating a virtual interface layer to connect high-level frameworks like TensorFlow, PyTorch, and ONNX with hardware designs. Two solutions will be explored: application-dependent FPGA designs and application-independent designs, like a soft-GPU, offering more flexibility for ML programmers.


In addition to the software framework, WP4 will define and execute a validation plan for testing the performance of selected ML algorithms on the FPGA implementations. Functional and performance tests will be conducted using a pre-selected dataset to evaluate the effectiveness of both the application-dependent FPGA and soft-GPU solutions in various space mission scenarios. The results will guide the final selection of the most suitable solutions for in-flight use.

Work Package Leader

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