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Data driven signal processing: an approach for energy efficient computing

Authors: Thucydides Xanthopoulos; V. Gutnik; Anantha P. Chandrakasan;

Data driven signal processing: an approach for energy efficient computing

Abstract

The computational switching activity of digital CMOS circuits can be dynamically minimized by designing algorithms that exploit signal statistics. This results in processors that have time-varying power requirements and perform computation on demand. An approach is presented to minimize the energy dissipation per data sample in variable-load DSP systems by adaptively minimizing the power supply voltage for each sample using a variable switching speed processor. In general, using buffering and filtering, the computation can be spread over multiple samples averaging the workload and lowering energy further. It is also shown that four levels of voltage quantization combined with dithering is sufficient to closely emulate arbitrary voltage levels.

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    popularity
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    Top 10%
    influence
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Powered by OpenAIRE graph
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
72
Top 10%
Top 1%
Top 1%
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