Hardware Evolution
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Hardware Evolution
Author: Adrian Thompson
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Evolution through natural selection has been going on for a very long time. Evolution through artificial selection has been practiced by humans for a large part of our history, in the breeding of plants and livestock. Artificial evolution, where we evolve an artifact through artificial selection, has been around since electronic computers became common: about 30 years. Right from the beginning, people have suggested using artificial evolution to design electronics automatically.l Only recently, though, have suitable re configurable silicon chips become available that make it easy for artificial evolution to work with a real, physical, electronic medium: before them, ex periments had to be done entirely in software simulations. Early research concentrated on the potential applications opened-up by the raw speed ad vantage of dedicated digital hardware over software simulation on a general purpose computer. This book is an attempt to show that there is more to it than that. In fact, a radically new viewpoint is possible, with fascinating consequences. This book was written as a doctoral thesis, submitted in September 1996. As such, it was a rather daring exercise in ruthless brevity. Believing that the contribution I had to make was essentially a simple one, I resisted being drawn into peripheral discussions. In the places where I deliberately drop a subject, this implies neither that it's not interesting, nor that it's not relevant: just that it's not a crucial part of the tale I want to tell here.
Hardware Evolution
""Hardware Evolution"" takes readers on a captivating journey through the Silicon Revolution, exploring how the evolution of computer hardware has fundamentally shaped our modern world. This accessible book illuminates the exponential growth of computing power, the remarkable miniaturization of electronic devices, and the democratization of technology. From the room-sized ENIAC of the 1940s to today's powerful smartphones, the book traces the rapid pace of technological change and its far-reaching consequences. The narrative is structured around three major sections: the rise of personal computing, the mobile revolution, and the Internet of Things. Each section demonstrates how hardware advancements have enabled new capabilities and transformed human behavior. For instance, the book highlights how Moore's Law has not only driven technological progress but also influenced business strategies and global economics. Readers will gain insight into how the microprocessor's invention revolutionized computing and how the evolution of digital cameras changed the way we capture and share memories. What sets this book apart is its engaging storytelling approach, which puts readers in the shoes of inventors and engineers. By weaving together technical concepts with anecdotes and real-world examples, ""Hardware Evolution"" makes complex topics both understandable and entertaining for a general audience interested in technology. The book concludes with a glimpse into emerging technologies like quantum computing, inviting readers to contemplate the future of hardware and its potential impact on society.
Adapting Hardware Systems by Means of Multi-Objective Evolution
Reconfigurable circuit devices have opened up a fundamentally new way of creating adaptable systems. Combined with artificial evolution, reconfigurable circuits allow an elegant adaptation approach to compensating for changes in the distribution of input data, computational resource errors, and variations in resource requirements. Referred to as "Evolvable Hardware" (EHW), this paradigm has yielded astonishing results for traditional engineering challenges and has discovered intriguing design principles, which have not yet been seen in conventional engineering. In this thesis, we present new and fundamental work on Evolvable Hardware motivated by the insight that Evolvable Hardware needs to compensate for events with different change rates. To solve the challenge of different adaptation speeds, we propose a unified adaptation approach based on multi-objective evolution, evolving and propagating candidate solutions that are diverse in objectives that may experience radical changes. Focusing on algorithmic aspects, we enable Cartesian Genetic Programming (CGP) model, which we are using to encode Boolean circuits, for multi-objective optimization by introducing a meaningful recombination operator. We improve the scalability of CGP by objectives scaling, periodization of local- and global-search algorithms, and the automatic acquisition and reuse of subfunctions using age- and cone-based techniques. We validate our methods on the applications of adaptation of hardware classifiers to resource changes, recognition of muscular signals for prosthesis control and optimization of processor caches.