Heat dissipation is a critical challenge facing the realization of emerging nanocomputing technologies. There are different components of this dissipation, and a part of it comes from the unavoidable cost of implementing logically irreversible operations. This stems from the fact that information is physical and manipulating it irreversibly requires energy. The unavoidable dissipative cost of losing information irreversibly fixes the fundamental limit on the minimum energy cost for computational strategies that utilize ubiquitous irreversible information processing.
A relation between the amount of irreversible information loss in a circuit and the associated energy dissipation was formulated by Landauer’s Principle in a technology-independent form. In a computing circuit, in addition to the information-theoretic dissipation, other physical processes that take place in association with irreversible information loss may also have an unavoidable thermodynamic cost that originates from the structure and operation of the circuit. In conventional CMOS circuits such unavoidable costs constitute only a minute fraction of the total power budget, however, in nanocircuits, it may be of critical significance due to the high density and operation speeds required. The lower bounds on energy, when obtained by considering the irreversible information cost as well as unavoidable costs associated with the operation of the underlying computing paradigm, may provide insight into the fundamental limitations of emerging technologies. This motivates us to study the problem of determining heat dissipation of computation in a way that reveals fundamental lower bounds on the energy cost for circuits realized in new computing paradigms.
In this talk, we introduce a physical-information-theoretic approach to determining minimum energy requirements of computation for concrete circuits realized within specific paradigms and discuss its application to prominent nanacomputing proposals such as Nano Application Specific Integrated Circuits (NASICs) and Quantum-dot Cellular Automata (QCA). We also comment on the role of fundamental lower bounds in technology assessment for determining the trends in nanoelectronic computing.
Short Bio: İlke Ercan earned her doctorate degree in February 2014 from Electrical and Computer Engineering Department at the University of Massachusetts, Amherst, under Professor Neal G. Anderson’s supervision. She has an M.S.E.C.E. with concentration in Electrophysics from the same department, a B.S. in Physics and an undergraduate minor degree in Philosophy and History of Science from Middle East Technical University, Ankara, Turkey. Upon completing her PhD, she worked as a Visiting Faculty at Smith College Picker Engineering Program in Spring and Fall 2014. She pursued her postdoctoral research under supervision of Professor Udo Schwalke, Institute for Semiconductor Technology and Nanoelectronics, and Professor Alfred Nordmann, Institute for Philosophy at TU Darmstadt in Spring and Summer 2015. She joined the Electrical and Electronics Engineering Department at Boğaziçi University in Fall 2015.