Dataflow Accelerator Architecture for Autonomous Machine Computing

Autor:	Liu, Shaoshan, Zhu, Yuhao, Yu, Bo, Gaudiot, Jean-Luc, Gao, Guang R.
Rok vydání:	2021
Předmět:	Computer Science - Hardware Architecture Computer Science - Artificial Intelligence Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	Commercial autonomous machines is a thriving sector, one that is likely the next ubiquitous computing platform, after Personal Computers (PC), cloud computing, and mobile computing. Nevertheless, a suitable computing substrate for autonomous machines is missing, and many companies are forced to develop ad hoc computing solutions that are neither principled nor extensible. By analyzing the demands of autonomous machine computing, this article proposes Dataflow Accelerator Architecture (DAA), a modern instantiation of the classic dataflow principle, that matches the characteristics of autonomous machine software. Comment: Please note that this may be a special case in that Professor Gao sadly passed away on September 12th, just as we had put the finishing touches on this submission
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2109.07047 Zobrazit plný text záznamu View this record from Arxiv