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Stanford University

Generalized Reversible Computing and the Unconventional Computing Landscape

Stanford University via YouTube

Overview

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Explore the frontiers of unconventional computing in this Stanford University seminar on Generalized Reversible Computing. Delve into the potential of reversible computing as a solution to the impending plateau in conventional digital computing efficiency. Examine various unconventional computing approaches, with a focus on how reversible computing could dramatically increase energy efficiency and performance. Learn about the speaker's background in nanotechnology, molecular computing, and reversible microprocessor design. Gain insights into topics such as neural computing, entropy, computational entropy, Landauer's Principle, logical reversibility, adiabatic circuits, and conditional reversible computing. Understand the importance of pursuing reversible computing for extracting greater economic value from computation in the future.

Syllabus

Introduction
Outline
Unconventional technologies
Neural computing
Entropy
Computational Entropy
Landeros Principle
Computing Entropy
Reversible Computing
Logical Reversibility
Landauers definition
Logical irreversible computations
Adiabatic circuits
Generalized Reversible Computing
Conditional Reversible Computing
Simulation Results
Resonator

Taught by

Stanford Online

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