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Author ORCID Identifier



Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Electrical and Computer Engineering

Year Degree Awarded


Month Degree Awarded


First Advisor

Neal G. Anderson

Second Advisor

Eric Polizzi

Third Advisor

Qiangfei Xia

Subject Categories

Electrical and Computer Engineering


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 nformation-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 work, we propose a physical-information-theoretic methodology that enables us to obtain such bounds for the minimum energy requirements of computation for concrete circuits realized within specific paradigms, and illustrate its application via prominent nanacomputing proposals. We begin by introducing the unavoidable heat dissipation problem and emphasize the significance of limitations it imposes on emerging technologies. We present the methodology developed to obtain the lower bounds on the unavoidable dissipation cost of computation for nanoelectronic circuits. We demonstrate our methodology via its application to various non-transistor-based (e.g. QCA) and transistor-based (e.g. NASIC) nanocomputing circuits. We also employ two CMOS circuits, in order to provide further insight into the application of our methodology by using this well-known conventional paradigm. We expand our methodology to modularize the dissipation analysis for QCA and NASIC paradigms, and discuss prospects for automation. We also revisit key concepts in thermodynamics of computation by focusing on the criticisms raised against the validity of Landauer's Principle. We address these arguments and discuss their implications for our methodology. We conclude by elaborating possible directions towards which this work can be expanded.