Relations Among Complexity Measures
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JouleTrack: a web based tool for software energy profiling
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Introduction to the Theory of Computation
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Introduction to Mathematical Theory of Computation
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Feynman Lectures on Computation
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Switching and Finite Automata Theory: Computer Science Series
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IEEE Transactions on Circuits and Systems II: Express Briefs
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OSC'10 Proceedings of the Third international conference on Optical supercomputing
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ACM Transactions on Design Automation of Electronic Systems (TODAES)
ARCS'12 Proceedings of the 25th international conference on Architecture of Computing Systems
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ARCS'12 Proceedings of the 25th international conference on Architecture of Computing Systems
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ACM Transactions on Embedded Computing Systems (TECS) - Special Section on Probabilistic Embedded Computing
Improving energy gains of inexact DSP hardware through reciprocative error compensation
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Models for characterizing noise based PCMOS circuits
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on ESTIMedia'10
Neural Network Guided Spatial Fault Resilience in Array Processors
Journal of Electronic Testing: Theory and Applications
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The main result in this paper establishes the energy savings derived by using probabilistic AND as well as NOT gates constructed from an idealized switch that produces a probabilistic bit (pbit). A probabilistic switch produces the desired value as an output that is 0 or 1 with probability p, represented as a pbit, and, hence, can produce the wrong output value with a probability of (1-p). In contrast with a probabilistic switch, a conventional deterministic switch produces a bit whose value is always correct. Our switch-based gate constructions are a particular case of a systematic methodology developed here for building energy-aware networks for computing, using pbits. Interesting examples of such networks include AND, OR, and NOT gates (or, as functions, Boolean conjunction, disjunction, and negation, respectively). To quantify the energy savings, novel measures of "technology independent驴 energy complexity are also introduced here驴these measures parallel conventional machine-independent notions of computational complexity such as the algorithm's running time and space. Networks of switches can be related to Turing machines and to Booleancircuits, both of which are widely known and well-understood models of computation. Our gate and network constructions lend substance to the following thesis (established for the first time by this author [1], [2], [3]): The mathematical technique referred to as randomization yieldingprobabilistic algorithms results in energy savings through a physical interpretation based on statistical thermodynamics and, hence, can serve as a basis for energy-aware computing. While the estimates of the energy saved through pbit--based probabilistic computing switches and networks developed here rely on the constructs and thermodynamic models due to Boltzmann, Gibbs, and Planck, this work has also led to the innovation of probabilistic CMOS-based devices and computing frameworks. Thus, for completeness, the relationship between the physical models on which this work is based and the electrical domain of CMOS-based switching will be discussed.