Overview

The Turing/von Neumann model of computing is dominant today but is by no means the only one. This textbook explores an important subset of alternatives, including those such as quantum and neuromorphic, which receive daily news attention. The models are organized into distinct groups. After a review of the Turing/von Neumann model to set the stage, the author discusses those that have their roots in the Turing/von Neumann model but perform potentially large numbers of computations in parallel; models that do away with the preplanned nature of the classical model and compute from just a statement of the problem; others that are simply mathematically different, such as probabilistic and reversible computation; models based on physical phenomena such as neurons; and finally those that leverage unique physical phenomena directly, such as quantum, optical, and DNA-based computing. Suggested readings provide a jumping-off point for deeper learning. A supplemental website contains chapters that did not make it into the book, as well as exercises, projects, and additional resources that will be useful for more in-depth investigations. The Zen of Exotic Computing is intended for computer science students interested in understanding alternative models of computing. It will also be of interest to researchers and practitioners interested in emerging technology such as quantum computing, machine learning, and AI.

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9781611977288

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Peter M. Kogge is the Ted H. McCourtney Professor of Computer Science and Engineering at the University of Notre Dame and a founder of Emu Solutions, now Lucata Inc. He is a retired IBM Fellow and a Fellow of both IEEE and AAAS. He holds over 40 patents and has authored three books on computing architecture and models of computation. Professor Kogge received the Daniel Slotnick best paper award (1994), the IEEE/ACM Seymour Cray award for high performance computer engineering (2012), the IEEE Charles Babbage award for contributions to the evolution of massively parallel processing architectures (2014), the Gauss best paper award for high performance computers, and the IEEE Computer Pioneer award (2015). His research interests are in massively parallel computing paradigms, processing in memory, and the relationship between massive nonnumeric applications, emerging technology, and computer architectures.

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