An Energy Efficient Real-Time Object Recognition Processor with Neuro-Fuzzy Controlled Workload-aware Task Pipelining

نویسندگان

  • Joo-Young Kim
  • Minsu Kim
  • Seungjin Lee
  • Jinwook Oh
  • Kwanho Kim
  • Jeong-Ho Woo
چکیده

An energy efficient pipelined architecture is proposed for multi-core object recognition processor. The proposed neuro-fuzzy controller and intelligent estimation of the workload of input video stream enable seamless pipelined operation of the 3 object recognition tasks. The neuro-fuzzy controller extracts the fine-grained region-of-interest, and its task pipelining achieves 60.6fps, 5.8x higher performance. The 8.1mJ/frame energy efficiency is obtained by workload aware task scheduling and power management, and it is 6.9x higher efficiency compared to the previous multi-core architectures. (

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تاریخ انتشار 2009