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Learning automata based energy-efficient AI hardware design for IoT applications

2020

Energy efficiency continues to be the core design challenge for artificial intelligence (AI) hardware designers. In this paper, we propose a new AI hardware architecture targeting Internet of Things applications. The architecture is founded on the principle of learning automata, defined using propositional logic. The logic-based underpinning enables low-energy footprints as well as high learning accuracy during training and inference, which are crucial requirements for efficient AI with long operating life. We present the first insights into this new architecture in the form of a custom-designed integrated circuit for pervasive applications. Fundamental to this circuit is systematic encodin…

7621003Computer scienceGeneral MathematicsDesign flow1006General Physics and Astronomy02 engineering and technologySoftwareRobustness (computer science)0202 electrical engineering electronic engineering information engineeringField-programmable gate arrayenergy efficiencyHardware architectureArtificial neural networkLearning automata52business.industryTsetlin machines020208 electrical & electronic engineeringGeneral Engineeringartificial intelligence hardware designArticlesneural networksAutomation020202 computer hardware & architecturebusinessComputer hardwareResearch ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences
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