Designing Reliable Nanoscale Circuits Using Principles Of Markov Random Fields

This book explains the application of recent advances in computational intelligence – algorithms, design methodologies, and synthesis techniques – to the design of integrated circuits and systems. It highlights new biasing and sizing approaches and optimization techniques and their application to the design of high-performance digital, VLSI, radio-frequency, and mixed-signal circuits and systems. This second of two related volumes addresses digital and network designs and applications, with 12 chapters grouped into parts on digital circuit design, network optimization, and applications. It will be of interest to practitioners and researchers in computer science and electronics engineering engaged with the design of electronic circuits.

As the MOSFET dimensions scale down to nanoscale level, the reliability of circuits based on these devices decreases. Therefore, a mechanism has to be devised that can make the nanoscale systems perform reliably using unreliable circuit components. The solution is fault-tolerant circuit design. Markov Random Field (MRF) is an effective approach that achieves fault-tolerance in integrated circuit design. The previous research on this technique suffers from limitations at the design, simulation and implementation levels. As improvements, the MRF fault-tolerance rules have been validated for a practical circuit example. The simulation framework is extended from thermal to a combination of thermal and random telegraph signal noise sources to provide a more rigorous noise environment for the simulation of nanoscale circuits. Moreover, an architecture-level improvement has been proposed in the design of previous MRF gates. The re-designed MRF is termed as Improved-MRF. By simulating various test circuits in Cadence, it is found that Improved-MRF circuits are 400 whereas MRF circuits are only 10 times more noise-tolerant than the CMOS alternatives.

Emerging Nanotechnologies: Test, Defect Tolerance and Reliability covers various technologies that have been developing over the last decades such as chemically assembled electronic nanotechnology, Quantum-dot Cellular Automata (QCA), and nanowires and carbon nanotubes. Each of these technologies offers various advantages and disadvantages. Some suffer from high power, some work in very low temperatures and some others need indeterministic bottom-up assembly. These emerging technologies are not considered as a direct replacement for CMOS technology and may require a completely new architecture to achieve their functionality. Emerging Nanotechnologies: Test, Defect Tolerance and Reliability brings all of these issues together in one place for readers and researchers who are interested in this rapidly changing field.

This book summarizes the state-of-the-art, regarding noise in nanometer semiconductor devices. Readers will benefit from this leading-edge research, aimed at increasing reliability based on physical microscopic models. Authors discuss the most recent developments in the understanding of point defects, e.g. via ab initio calculations or intricate measurements, which have paved the way to more physics-based noise models which are applicable to a wider range of materials and features, e.g. III-V materials, 2D materials, and multi-state defects. Describes the state-of-the-art, regarding noise in nanometer semiconductor devices; Enables readers to design more reliable semiconductor devices; Offers the most up-to-date information on point defects, based on physical microscopic models.

This book provides a single-source reference to one of the more challenging reliability issues plaguing modern semiconductor technologies, negative bias temperature instability. Readers will benefit from state-of-the art coverage of research in topics such as time dependent defect spectroscopy, anomalous defect behavior, stochastic modeling with additional metastable states, multiphonon theory, compact modeling with RC ladders and implications on device reliability and lifetime.

Experts review the latest research on the neocortex and consider potential directions for future research. Over the past decade, technological advances have dramatically increased information on the structural and functional organization of the brain, especially the cerebral cortex. This explosion of data has radically expanded our ability to characterize neural circuits and intervene at increasingly higher resolutions, but it is unclear how this has informed our understanding of underlying mechanisms and processes. In search of a conceptual framework to guide future research, leading researchers address in this volume the evolution and ontogenetic development of cortical structures, the cortical connectome, and functional properties of neuronal circuits and populations. They explore what constitutes “uniquely human” mental capacities and whether neural solutions and computations can be shared across species or repurposed for potentially uniquely human capacities. Contributors Danielle S. Bassett, Randy M. Bruno, Elizabeth A. Buffalo, Michael E. Coulter, Hermann Cuntz, Stanislas Dehaene, James J. DiCarlo, Pascal Fries, Karl J. Friston, Asif A. Ghazanfar, Anne-Lise Giraud, Joshua I. Gold, Scott T. Grafton, Jennifer M. Groh, Elizabeth A. Grove, Saskia Haegens, Kenneth D. Harris, Kristen M. Harris, Nicholas G. Hatsopoulos, Tarik F. Haydar, Takao K. Hensch, Wieland B. Huttner, Matthias Kaschube, Gilles Laurent, David A. Leopold, Johannes Leugering, Belen Lorente-Galdos, Jason N. MacLean, David A. McCormick, Lucia Melloni, Anish Mitra, Zoltán Molnár, Sydney K. Muchnik, Pascal Nieters, Marcel Oberlaender, Bijan Pesaran, Christopher I. Petkov, Gordon Pipa, David Poeppel, Marcus E. Raichle, Pasko Rakic, John H. Reynolds, Ryan V. Raut, John L. Rubenstein, Andrew B. Schwartz, Terrence J. Sejnowski, Nenad Sestan, Debra L. Silver, Wolf Singer, Peter L. Strick, Michael P. Stryker, Mriganka Sur, Mary Elizabeth Sutherland, Maria Antonietta Tosches, William A. Tyler, Martin Vinck, Christopher A. Walsh, Perry Zurn