A bottom-up methodology for the fast assessment of cnn mappings on energy-efficient accelerators

HIGHLIGHTS

  • who: Guillaume Devic et al. from the UnivMontpellier, CNRS, Montpellier, France have published the article: A Bottom-Up Methodology for the Fast Assessment of CNN Mappings on Energy-Efficient Accelerators, in the Journal: (JOURNAL)
  • what: The authors propose a design methodology by combining different ion levels to quickly address the mapping of convolutional neural networks ML Starting from an opensource core adopting the RISC-V instruction set architecture the authors define in RTL a more flexible and powerful multiply-and-accumulate (MAC) unit compared to the native MAC unit. The aim of this paper is . . .

     

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