BDD Minimization for Approximate Computing

We present <i>Approximate BDD Minimization</i> (ABM) as a problem that has application in approximate computing. Given a BDD representation of a multi-output Boolean function, ABM asks whether there exists another function that has a smaller BDD representation but meets a threshold w.r.t. an error metric. We present operators to derive approximated functions and present algorithms to exactly compute the error metrics directly on the BDD representation. An experimental evaluation demonstrates the applicability of the proposed approaches.


Published in:
Proceedings of the 21st Asia and South Pacific Design Automation Conference (ASP-DAC 2016), 474-479
Presented at:
21st Asia and South Pacific Design Automation Conference (ASP-DAC 2016), Macao SAR, China, January 25-28, 2016
Year:
2016
Publisher:
New York, IEEE
ISBN:
978-1-4673-9569-4
Laboratories:




 Record created 2016-02-16, last modified 2018-09-13

n/a:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)