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Architecture and CAD for Deep-Submicron FPGAs
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DRAM Circuit Design: A Tutorial
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Finite State Machine Synthesis with Concurrent Error Detection
ITC '99 Proceedings of the 1999 IEEE International Test Conference
Nanowire-based sublithographic programmable logic arrays
FPGA '04 Proceedings of the 2004 ACM/SIGDA 12th international symposium on Field programmable gate arrays
Fundamentals of Applied Probability Theory
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A Mathematical Theory of Communication
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IEEE Transactions on Nanotechnology
Stochastic assembly of sublithographic nanoscale interfaces
IEEE Transactions on Nanotechnology
Logic synthesis of multilevel circuits with concurrent error detection
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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ACM Journal on Emerging Technologies in Computing Systems (JETC)
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ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Fault tolerant nano-memory with fault secure encoder and decoder
Proceedings of the 2nd international conference on Nano-Networks
Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation
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Challenges in scalable fault tolerance
NANOARCH '09 Proceedings of the 2009 IEEE/ACM International Symposium on Nanoscale Architectures
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To date we have relied on the "Law of Large Numbers" below the device level to guarantee deterministic device behavior (e.g. dopant ratios, transition timing, electron state storage). However, at the nanoscale, we hope to build devices with small numbers of atoms or molecules (e.g. wires which are 3-10 atoms wide, diodes built from 1-10 molecules), and we hope to store state with small numbers of electrons (e.g. 10's). If we are to build devices at these scales, we will no longer be able to rely on the "Law of Large Numbers" below the device level. We must, instead, employ the "Law of Large Numbers" above the device level in order to obtain predictable behavior from atomic-scale phenomena which are statistical in nature. At the same time, the "Law of Large Numbers" can also help us by providing statistical differentiation at scales smaller than those we can pattern directly or economically using lithography. In this chapter, we examine various applications of the "Law of Large Numbers" above the device level to build reliable and controllable systems from nanoscale devices and processes that only have statistically predictable behavior.