Open AccessImplementation of Accelerating Video Preprocessing based on ZYNQ Platform Resource Management
Author(s) -
Mengxue Sheng,
Wanwan Hou,
Juchao Jiang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1544/1/012112
Subject(s) - computer science , field programmable gate array , embedded system , schedule , preprocessor , process (computing) , video game , software deployment , architecture , real time computing , operating system , artificial intelligence , multimedia , art , visual arts
Embedded AI rised in recent years, AI algorithm deployment platforms need strong computing power, but embedded systems focus on the balance between performance and cost. The contradiction has become a great challenge for the development of embedded AI. This paper analyzes the “ARM+FPGA” architecture and NEON register resources of the ZYNQ series chips introduced by Xilinx, and proposes a method to reasonably schedule the above resources to accelerate video preprocessing when it is used as an edge processing platform for intelligent monitoring terminals. This method makes the video intelligent analysis process of the monitoring terminal achieve real-time.