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Defect-Aware Nanocrossbar Logic Mapping through Matrix Canonization Using Two-Dimensional Radix Sort SEZER GOREN, Yeditepe University H. FATIH UGURDAG, Ozyegin University OKAN PALAZ, Bahcesehir University Nanocrossbars (i.e., nanowire crossbars) offer extreme logic densities but come with very high defect rates; stuck-open/closed, broken nanowires. Achieving reasonable yield and utilization requires logic mapping that is defect-aware even at the crosspoint level. Such logic mapping works with a defect map per each manufactured chip. The problem can be expressed as matching of two bipartite graphs; one for the logic to be implemented and other for the nanocrossbar. This article shows that the problem becomes a Bipartite SubGraph Isomorphism (BSGI) problem within sub-nanocrossbars free of stuck-closed faults. Our heuristic KNS-2DS is an iterative rough canonizer with approximately O(N2 ) complexity followed by an O(N3 ) matching algorithm. Canonization brings a partial or full order to graph nodes. It is normally used for solving the regular Graph Isomorphism (GI) problem, while we apply it to BSGI. KNS stands for K-Neighbor Sort and is used for initializing our main contribution 2-Dimensional-Sort (2DS). 2DS operates on the adjacency matrix of a bipartite graph. Radix-2 2DS solves the problem in the absence of stuck-closed faults. With the
ACM Journal on Emerging Technologies in Computing Systems (JETC) – Association for Computing Machinery
Published: Aug 1, 2011
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