Reducing FPGA algorithm area by avoiding redundant computation

  • Axelrod B
  • Laverne M
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Abstract

We develop a new paradigm for designing fully streaming, area-efficient FPGA implementations of common building blocks for vision algorithm. By focusing on avoiding redundant computation we achieve a reduction of one to two orders of magnitude reduction in design area utilization as compared to previous implementations. We demonstrate that our design works in practice by building five 325 frames per second, high resolution Harris corner detection cores onto a single FPGA.

Author-supplied keywords

  • Accelerator
  • Convolution
  • FPGA
  • Harris corner
  • Non-max suppression
  • Vision

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Authors

  • Brian Axelrod

  • Michel Laverne

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