Abstract
In this paper, architecture of a Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v2) is given and the implementation results are discussed. The proposed architecture has a fully pipelined structure, capable of processing full-HD 1080p@60 (1920 × 1080 resolution at 60 Hz frame rate, 124.4 MHz visible pixel rate) video streams, which is implemented on both high-end and low-cost FPGA devices, Altera Stratix IV GX 230, and Cyclone III C 25, respectively. Many features of the architecture are designed to be either pre-synthesis configurable or runtime programmable, which makes the processor extremely flexible, reusable, scalable, and practical.
Keywords
Stratix
Computer science
Frame rate
Field-programmable gate array
Scalability
Embedded system
Computer hardware
Architecture
Frame (networking)
Computer architecture
Throughput
Pixel
Real-time computing
Operating system
Computer network
Artificial intelligence
Subject Areas
Neural Networks Stability and Synchronization
·Computer Networks and Communications ·Physical Sciences
Advanced Memory and Neural Computing
·Electrical and Electronic Engineering ·Physical Sciences
Neural Networks and Applications
·Artificial Intelligence ·Physical Sciences
Citations by Year
2014: 2
2015: 2
2016: 7
2017: 8
2018: 5
2019: 3
2025: 3
OpenAlex SDG Match
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Affordable and clean energy 45%
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