Type of Document	Dissertation
Author	Zheng, Yexin
Author's Email Address	yexin@vt.edu
URN	etd-12082009-135511
Title	Circuit Design Methods with Emerging Nanotechnologies
Degree	PhD
Department	Electrical and Computer Engineering
Advisory Committee	Advisor Name Title Huang, Chao Committee Chair Cao, Yang Committee Member Hsiao, Michael S. Committee Member Schaumont, Patrick Robert Committee Member Yang, Yaling Committee Member
Keywords	design automation ant colony optimization satisfiability equivalence checking defect tolerance logic synthesis nanotechnology circuit design
Date of Defense	2009-12-08
Availability	unrestricted
Abstract As complementary metal-oxide semiconductor (CMOS) technology faces more and more severe physical barriers down the path of continuously feature size scaling, innovative nano-scale devices and other post-CMOS technologies have been developed to enhance future circuit design and computation. These nanotechnologies have shown promising potentials to achieve magnitude improvement in performance and integration density. The substitution of CMOS transistors with nano-devices is expected to not only continue along the exponential projection of Moore's Law, but also raise significant challenges and opportunities, especially in the field of electronic design automation. The major obstacles that the designers are experiencing with emerging nanotechnology design include: i) the existing computer-aided design (CAD) approaches in the context of conventional CMOS Boolean design cannot be directly employed in the nanoelectronic design process, because the intrinsic electrical characteristics of many nano-devices are not best suited for Boolean implementations but demonstrate strong capability for implementing non-conventional logic such as threshold logic and reversible logic; ii) due to the density and size factors of nano-devices, the defect rate of nanoelectronic system is much higher than conventional CMOS systems, therefore existing design paradigms cannot guarantee design quality and lead to even worse result in high failure ratio. Motivated by the compelling potentials and design challenges of emerging post-CMOS technologies, this dissertation work focuses on fundamental design methodologies to effectively and efficiently achieve high quality nanoscale design. A novel programmable logic element (PLE) is first proposed to explore the versatile functionalities of threshold gates (TGs) and multi-threshold threshold gates (MTTGs). This PLE structure can realize all three- or four-variable logic functions through configuring binary control bits. This is the first single threshold logic structure that provides complete Boolean logic implementation. Based on the PLEs, a reconfigurable architecture is constructed to offer dynamic reconfigurability with little or no reconfiguration overhead, due to the intrinsic self-latching property of nanopipelining. Our reconfiguration data generation algorithm can further reduce the reconfiguration cost. To fully take advantage of such threshold logic design using emerging nanotechnologies, we also developed a combinational equivalence checking (CEC) framework for threshold logic design. Based on the features of threshold logic gates and circuits, different techniques of formulating a given threshold logic in conjunctive normal form (CNF) are introduced to facilitate efficient SAT-based verification. Evaluated with mainstream benchmarks, our hybrid algorithm, which takes into account both input symmetry and input weight order of threshold gates, can efficiently generate CNF formulas in terms of both SAT solving time and CNF generating time. Then the reversible logic synthesis problem is considered as we focus on efficient synthesis heuristics which can provide high quality synthesis results within a reasonable computation time. We have developed a weighted directed graph model for function representation and complexity measurement. An atomic transformation is constructed to associate the function complexity variation with reversible gates. The efficiency of our heuristic lies in maximally decreasing the function complexity during synthesis steps as well as the capability to climb out of local optimums. Thereafter, swarm intelligence, one of the machine learning techniques is employed in the space searching for reversible logic synthesis, which achieves further performance improvement. To tackle the high defect-rate during the emerging nanotechnology manufacturing process, we have developed a novel defect-aware logic mapping framework for nanowire-based PLA architecture via Boolean satisfiability (SAT). The PLA defects of various types are formulated as covering and closure constraints. The defect-aware logic mapping is then solved efficiently by using available SAT solvers. This approach can generate valid logic mapping with a defect rate as high as 20%. The proposed method is universally suitable for various nanoscale PLAs, including AND/OR, NOR/NOR structures, etc. In summary, this work provides some initial attempts to address two major problems confronting future nanoelectronic system designs: the development of electronic design automation tools and the reliability issues. However, there are still a lot of challenging open questions remain in this emerging and promising area. We hope our work can lay down stepstones on nano-scale circuit design optimization through exploiting the distinctive characteristics of emerging nanotechnologies.
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