Prof. Ing. Lukáš Sekanina, Ph.D.
VAVERKA Filip, HRBÁČEK Radek and SEKANINA Lukáš. Evolving Component Library for Approximate High Level Synthesis. In: 2016 IEEE Symposium Series on Computational Intelligence. Athens: IEEE Computational Intelligence Society, 2016, pp. 18. ISBN 9781509042401.  Publication language:  english 

Original title:  Evolving Component Library for Approximate High Level Synthesis 

Title (cs):  Evoluční návrh knihovny komponent pro vysokoúrovňovou syntézu 

Pages:  18 

Proceedings:  2016 IEEE Symposium Series on Computational Intelligence 

Conference:  IEEE Symposium Series on Computational Intelligence 2016 

Place:  Athens, GR 

Year:  2016 

ISBN:  9781509042401 

DOI:  10.1109/SSCI.2016.7850168 

Publisher:  IEEE Computational Intelligence Society 

Files:  

 Keywords 

approximate computing, cartesian genetic programming, evolutionary algorithms, multiobjective optimization, high level synthesis

Annotation 

An approximate computing approach has recently been introduced for high level circuit synthesis (HLS) in order to make good use of approximate circuits at system and block level. It is assumed in HLS algorithms that a component library containing various implementations of elementary circuit components is available. An open problem is how to construct such a component library in the context of approximate computing, where the component's error is a new design variable and hence many compromise implementations exist for a given component. In this paper, we first introduce a multiobjective Cartesian genetic programming method to create a comprehensive component library containing hundreds of Pareto optimal implementations of approximate 8bit adders and multipliers, where the error, area and delay are simultaneously optimized. Another multiobjective evolutionary algorithm is employed to solve the so called binding problem of HLS, in which suitable approximate components are assigned to nodes of the data flow graph describing a complex digital circuit. Two approaches are then proposed and compared in order to reduce the size of the library of approximate components. It is shown that a random subsampling of the component library provides satisfactory results in the context of our study. The proposed methods are evaluated using two benchmark circuits  the reduce (sum) and DCT circuits. 
BibTeX: 

@INPROCEEDINGS{
author = {Filip Vaverka and Radek Hrb{\'{a}}{\v{c}}ek and
Luk{\'{a}}{\v{s}} Sekanina},
title = {Evolving Component Library for Approximate High
Level Synthesis},
pages = {18},
booktitle = {2016 IEEE Symposium Series on Computational Intelligence},
year = 2016,
location = {Athens, GR},
publisher = {IEEE Computational Intelligence Society},
ISBN = {9781509042401},
doi = {10.1109/SSCI.2016.7850168},
language = {english},
url = {http://www.fit.vutbr.cz/research/view_pub.php.en?id=11231}
} 
