合写作者：Ning, Zhaolong,Hou, Weigang,Hu, Bin,Guo, Pengxing
发表刊物：IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
关键字：Computer architecture design; optical network-on-chip (ONoC); service-demand matching; sharing economy
摘要：In sharing economy, people offer idle social resources to others in a sharing manner. Through community-based online platforms, the people offering services can earn commission while others can enjoy a better life via renting social resources. Consequently, the value-in-use of services is expectedly strengthened within the unit time, although the total amount of social resources remains constant. Influenced by sharing economy, some famous companies have developed intelligent systems to analyze the most appropriate coincidence between citizens' idle supply and renting demand from numerous data sets. However, the big data analysis of the optimal service-demand matching usually runs on the traditional multiprocessors equipped in intelligent systems, so-called "system-on-chip." In this paper, we design a novel computer architecture-the accelerator based on optical network-on-chip (ONoC)-to further speed up the matching between citizens' offer and demand in sharing economy. Our ONoC-based accelerator is able to quickly calculate the optimal service-demand matching by processing computation tasks on parallel cores, i.e., task-core mapping. In addition, to improve the accelerator reliability, the assorted task-core mapping algorithm is also designed. The extensive simulation results based on real trace file demonstrate the effectiveness of our system and algorithm.