Intelligent Network-on-Chip With Online Reinforcement Learning for Portable HD Object Recognition Processor

Autor:	Byeong-Gyu Nam, Hoi-Jun Yoo, Gyeonghoon Kim, Injoon Hong, Junyoung Park
Rok vydání:	2014
Předmět:	Bandwidth allocation Intelligent Network Network on a chip business.industry Computer science Embedded system Feature extraction Cognitive neuroscience of visual object recognition Bandwidth (computing) Reinforcement learning Throughput Electrical and Electronic Engineering business
Zdroj:	IEEE Transactions on Circuits and Systems I: Regular Papers. 61:476-484
ISSN:	1558-0806 1549-8328
DOI:	10.1109/tcsi.2013.2284188
Popis:	An intelligent Reinforcement Learning (RL) Network-on-Chip (NoC) is proposed as a communication architecture of a heterogeneous many-core processor for portable HD object recognition. The proposed RL NoC automatically learns bandwidth adjustment and resource allocation in the heterogeneous many-core processor without explicit modeling. By regulating the bandwidth and reallocating cores, the throughput performances of feature detection and description are increased by 20.4% and 11.5%, respectively. As a result, the overall execution time of the object recognition is reduced by 38%. The proposed processor with RL NoC is implemented in a 65 nm CMOS process, and it successfully demonstrates the real-time object recognition for a 720 p HD video stream while consuming 235 mW peak power at 200 MHz, 1.2 V.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::40122fc6c214da6a82061ff6c95b23f1 https://doi.org/10.1109/tcsi.2013.2284188 Zobrazit plný text záznamu