Prof. Ing. Lukáš Sekanina, Ph.D.

VAŠÍČEK Zdeněk, MRÁZEK Vojtěch a SEKANINA Lukáš. Automated Circuit Approximation Method Driven by Data Distribution. In: Design, Automation and Test in Europe Conference. TBA, 2019, s. 1-6.
Jazyk publikace:angličtina
Název publikace:Automated Circuit Approximation Method Driven by Data Distribution
Strany:1-6
Sborník:Design, Automation and Test in Europe Conference
Konference:Design, Automation and Test in Europe Conference
Místo vydání:TBA, US
Rok:2019
Soubory: 
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Anotace
We propose an application-tailored data-driven fully automated method for functional approximation of combinational circuits. We demonstrate how an application-level error metric such as the classification accuracy can be translated to a component-level error metric needed for an efficient and fast search in the space of approximate low-level components that are used in the application. This is possible by employing a weighted mean error distance (WMED) metric for steering the circuit approximation process which is conducted by means of genetic programming. WMED introduces a set of weights (calculated from the data distribution measured on a selected signal in a given application) determining the importance of each input vector for the approximation process. The method is evaluated using synthetic benchmarks and application-specific approximate MAC (multiply-and-accumulate) units that are designed to provide the best trade-offs between the classification accuracy and power consumption of two image classifiers based on neural networks.
BibTeX:
@INPROCEEDINGS{
   author = {Zden{\v{e}}k Va{\v{s}}{\'{i}}{\v{c}}ek and
	Vojt{\v{e}}ch Mr{\'{a}}zek and Luk{\'{a}}{\v{s}}
	Sekanina},
   title = {Automated Circuit Approximation Method Driven by
	Data Distribution},
   pages = {1--6},
   booktitle = {Design, Automation and Test in Europe Conference},
   year = {2019},
   location = {TBA, US},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.cs?id=11821}
}

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