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The 3D integrated circuit (3D-IC) is garnering significant attention from academia and industry as a key technology leading the post-Moore era, offering new levels of efficiency, power, performance, and form-factor advantages to the semiconductor industry. However, thermal management in 3D-ICs presents a critical challenge that must be overcome to ensure prosperity for this technology. Unlike traditional thermal management solutions that perceive heat generation in 3D-ICs negatively and aim to eliminate it, this paper proposes, for the first time, a thermal management method that positively utilizes heat to achieve low-power operation in 3D-ICs. This approach is based on a novel discovery that circuits can reduce power consumption at higher temperatures by leveraging the temperature effect inversion (TEI) phenomenon in ultralow-voltage (ULV) operating circuits, a characteristic of low-power techniques (TEI-LP techniques). Along with a detailed explanation of this discovery, this paper introduces new thermal management technologies for practical application in 3D-ICs. Furthermore, to achieve optimal energy efficiency with the proposed technology, we develop a temperature controller essential for this purpose. The developed controller is a deep learning-based PID autotuner. This paper proves the theoretical validity of the AI control algorithm designed for this purpose and demonstrates the functional correctness and power-saving effectiveness of the developed controller through intensively conducted simulations. [ABSTRACT FROM AUTHOR]

P.M. Pu and Y.M. Liu extended Moore-Smith's convergence of nets to fuzzy topology and Y.M. Liu provided analogous results to J. Kelley's classical characterization theorem of net convergence by introducing the notion of fuzzy convergence classes. In a previous paper, the authors of this study provided modified versions of this characterization by using an alternative notion of convergence of fuzzy nets, introduced by B.M.U. Afsan, named fuzzy net ideal convergence. Our main scope here is to generalize and simplify the preceding results. Specifically, we insert the concept of a fuzzy function ideal convergence class, L , on a non-empty set, X, consisting of triads (f , e , I) , where f is a function from a non-empty set, D, to the set FP (X) of fuzzy points in X, which we call fuzzy function, e ∈ FP (X) , and I is a proper ideal on D, and we provide necessary and sufficient conditions to establish the existence of a unique fuzzy topology, δ , on X, such that (f , e , I) ∈ L iff f I -converges to e, relative to the fuzzy topology δ. [ABSTRACT FROM AUTHOR]