%0 Journal Article
%@ 0278-0070
%A Dang, Nam Khanh
%A Ahmed, Akram Ben
%A Abdallah, Abderazek Ben
%A Tran, Xuan Tu
%D 2021
%F SisLab:4430
%I IEEE
%J IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
%T HotCluster: A thermal-aware defect recovery  method for Through-Silicon-Vias Towards Reliable  3-D ICs systems
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4430/
%X Through Silicon Via (TSV) is considered as the  near-future solution to realize low-power and high-performance  3D-Integrated Circuits (3D-ICs) and 3D-Network-on-Chips (3DNoCs). However, the lifetime reliability issue of TSV due to  its fault sensitivity and the high operating temperature of  3D-ICs, which also accelerates the fault-rate, is one of the  most critical challenges. Meanwhile, most current works focus  on detecting and correcting TSV defects after manufacturing  without considering high-temperature nodes’ impact on lifetime  reliability. Besides, the recovery for defective clusters is also  challenging because of costly redundancies. In this work, we  present HotCluster: a hotspot-aware self-correction platform for  clustering defects in 3D-NoCs to help understand and tackle  this problem. We first give a method to predict normalized fault  rates and place redundant TSV groups according to each region’s  fault rate. In our particular medium fault-rate (normalized to the  coolest area), HotCluster reduces about 60% of the redundancies  in comparison to the uniformly distributed redundancies while  having a higher ratio of router working in a normal state. Furthermore, HotCluster integrates both online (weight-based) and  offline (max-flow min-cut offline method) mapping algorithms to  help the system correct the faulty TSV clusters. The experimental  results show that both the max-flow min-cut offline method and  weight-based online mode with a redundancy of 0.25 exhibits less  than 1% of routers disabled under 50% defect-rates.