Molecular electronics: devices, systems and tools for gigagate, gigabit chips
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Nanowire-based sublithographic programmable logic arrays
FPGA '04 Proceedings of the 2004 ACM/SIGDA 12th international symposium on Field programmable gate arrays
Nanowire-based programmable architectures
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Topology aware mapping of logic functions onto nanowire-based crossbar architectures
Proceedings of the 43rd annual Design Automation Conference
Application-independent defect tolerance of reconfigurable nanoarchitectures
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Defect-tolerant Logic with Nanoscale Crossbar Circuits
Journal of Electronic Testing: Theory and Applications
Defect tolerance in QCA-based PLAs
NANOARCH '08 Proceedings of the 2008 IEEE International Symposium on Nanoscale Architectures
Defect-Tolerant Logic Mapping on Nanoscale Crossbar Architectures and Yield Analysis
DFT '09 Proceedings of the 2009 24th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems
Array-based architecture for FET-based, nanoscale electronics
IEEE Transactions on Nanotechnology
Stochastic assembly of sublithographic nanoscale interfaces
IEEE Transactions on Nanotechnology
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Crossbar architectures are promising in the emerging nanoscale electronic environment. Logic mapping onto highly defective crossbars emerges as a fundamental challenge and defect tolerance techniques therefore become crucially important. In this paper we investigate the most challenging part of the problem-the exponential runtime inevitably involved in finding a valid mapping. Runtime depends on solution density of the searching space. Yet, the complexity of the problem is caused by the correlations in the searching space. When defect rate is trivially low, such impact is negligible. When defect rate increases, correlations drive up runtime by not only decreasing the expectation of solution density, but also increasing the standard deviation. Consequently, runtime improvement can be achieved through means which reduce the correlations in the solution space.