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    Luo Zuying, Zhang Yubin, Yu Xianchuan. A Single Open-Defect Analysis Method for Power/Ground Networks[J]. Journal of Computer Research and Development, 2009, 46(7): 1234-1240.
    Citation: Luo Zuying, Zhang Yubin, Yu Xianchuan. A Single Open-Defect Analysis Method for Power/Ground Networks[J]. Journal of Computer Research and Development, 2009, 46(7): 1234-1240.

    A Single Open-Defect Analysis Method for Power/Ground Networks

    • With IC technology scaling down into nanometer regime, voltage disturbances severely influence the performance of VLSI circuits. Both via mismatches in manufacture and electro-migrations of Cu interconnect wires in working ICs may provide many candidates for open defects in power/ground networks, which in turn significantly impacts voltage disturbances. In order to quickly test these open defects, it is imperative to efficiently analyze the defects’ influences on P/G networks. Therefore, a single defect successive over-relaxation algorithm (SD-SOR) is firstly proposed in this paper to fast analyze nodal voltage drop distributions of P/G networks resulted from single open defect. Based on the voltage distribution of a defect-free P/G network, SD-SOR only needs to relax on a few nodes that surround the defect and thus suffer visible influences from the defect. Compared with the traditional global SOR method that orderly relaxes all nodes, SD-SOR shows the following advantages. The first advantage is locality. For each open defect, SD-SOR relaxes from the nodes connected with the defect to those surrounding nodes as wave transmission, while the wave stops at the nodes whose IR droop variation is less than a pre-assigned threshold. The second one is efficiency. SD-SOR not only relaxes a small part of the nodes in P/G networks but also needs much less relaxation iterations. The third one is high accuracy. Because most nodes are far away from the defect and suffer invisible influences, SD-SOR can obtain high enough accuracy through relaxing only a few surrounding nodes. Experimental ressults show that the proposed SD-SOR method is 57 times faster than the pre-conditional global SOR method with a maximum error of 0.95%.
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