Abstract
In this paper the utilization of neural processors as supervisory units that control predictive techniques of dynamic power management is described. Power management becomes more and more important as density of power dissipated in modern integrated circuits, especially microprocessors, continuously raises and can be even higher than 4 megawatts per square meter. It causes temperature increases that might be dangerous for the chip. The presented supervisors that are based on neurons allow correct prediction of chip temperature on the basis of current temperature, power losses that will be consumed in the next units of time, as well as previous power dissipations. Their task is to keep the throughput of high-frequency and high-efficiency systems on the highest possible level under the conditions of energy savings and maintaining safe temperature of chip. The supervisory units are designed using 32-bit and fixed-point precision.
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Gołda, A., Kos, A. (2008). Neural Processor as a Dynamic Power Manager for Digital Systems. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_32
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DOI: https://doi.org/10.1007/978-3-540-88636-5_32
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