Since the three-dimensional Network on Chip(3D NoC)uses through-silicon via technology to connect the chips,each silicon layer is conducted through heterogeneous thermal,and 3D NoC system suffers from thermal problems.To alleviate the seriousness of the thermal problem,the distribution of data packets usually relies on traffic information or historical temperature information.However,thermal problems in 3D NoC cannot be solved only based on traffic or temperature information.Therefore,we propose a Score-Based Traffic-and Thermal-Aware Adaptive Routing(STTAR)that applies traffic load and temperature information to routing.First,the STTAR dynamically adjusts the input and output buffer lengths of each router with traffic load information to limit routing resources in overheated areas and control the rate of temperature rise.Second,STTAR adopts a scoring strategy based on temperature and the number of free slots in the buffer to avoid data packets being transmitted to high-temperature areas and congested areas and to improve the rationality of selecting routing output nodes.In our experiments,the proposed scoring Score-Based Traffic-and Thermal-Aware Adaptive Routing(STTAR)scheme can increase the throughput by about 14.98%to 47.90%and reduce the delay by about 10.80%to 35.36%compared with the previous works.
Juan FangYunfei MaoMin CaiLi’ang ZhaoHuijie ChenWei Xiang
为了降低动态环境对同时定位与建图(simultaneous localization and mapping,SLAM)位姿估计的干扰,提出一种将目标检测网络与ORB-SLAM2系统结合的方法.在帧间估计阶段,使用目标检测网络获取当前帧的语义信息,得到潜在可移动物体边界框,结合深度图像并根据最大类间方差算法分割出边界框内前景,把落在前景中的动态特征点剔除,利用剩下的特征点估计位姿.在回环检测阶段,利用边界框构建图像语义特征,并与历史帧比较,查询相似关键帧,与视觉词袋法相比,该方法查询速度快,内存占用少.在TUM Techni数据集上进行测试,结果表明该方法可以有效提高ORB-SLAM2在高动态场景中的性能.
