Deep Learning Accelerator on Programmable Heterogeneous System with RISC-V Processor

Published in 42rd International Convention on Information and Communication Technology, Electronics and Microelectronics, 2019

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This paper explores a heterogeneous, open source, RISC-V based platform, called PULP (Parallel Ultra-Low-Power Processing Platform) with customizable MAC (multiply and accumulate) accelerator for neural network acceleration on edge computing devices with low power and performance-limited resources. To address the performance and power constraints we propose binarized implementation of a neural network accelerator. We show that binarized implementation is faster than the fixed-point accelerated implementation, albeit with some loss in precision, but still applicable to most of the use cases in edge computing.

    author = {Strizic, Luka and Pervan, Branimir and Knezovic, Josip},
    booktitle = {2019 proceedings of the 42nd international convention MIPRO},
    pages = {1126--1131},
    publisher = {IEEE},
    title = ,
    url = {},
    year = {2019}