Project

MANIAC

BDD Manipulation for Approximate Computing

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The project MANIAC aims to optimise algorithms for approximate computing on the basis of binary decision diagrams. Approximate computing (AC) exploits the capability of many applications to tolerate a certain level of inexactness in computations. Because the result does not have to precise, a much better degree of efficiency can be reached. For example, when processing multi-media content, certain degrees of approximation are tolerated, as the human user does not notice minimal differences in hue or pitch. The approximate computing paradigm results in new requirements on the design process of hardware systems, which CPS scientists aim to meet by using binary decision diagrams (BDDs). BDDs are data structures to represent boolean functions, which are already being employed in hardware design – for example for logic synthesis or verification. In the project MANIAC, BDDs will allow an efficient representation of functions which in the long run will be tolerant against many kinds of deviations, and will thereby improve the design of new, powerful technologies.

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Publications about the project

Daniel Große, Rolf Drechsler

In: Design, Automation and Test in Europe (DATE). Design, Automation & Test in Europe (DATE-2019) March 25-29 Florence Italy 2019.

To the publication
Saeideh Shirinzadeh, Rolf Drechsler

In: IEEE Computer Society Annual Symposium on VLSI (ISVLSI) 2019. IEEE Computer Society Annual Symposium on VLSI (ISVLSI-2019) July 15-17 Miami Florida United States 2019.

To the publication
Daniel Große, Rolf Drechsler

In: Euromicro Conference on Digital System Design (DSD). Euromicro Conference on Digital System Design (DSD-2018) August 29-31 Prague Czech Republic 2018.

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German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz