Design Space Exploration of Multi-output Logic Function Approximations

Approximate Computing has emerged as a design paradigm that allows to decrease hardware costs by reducing the accuracy of the computation for applications that are robust against such errors. In Boolean logic approximation, the number of terms and literals of a logic function can be reduced by allow...

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Vydáno v:2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) s. 1 - 8
Hlavní autoři: Echavarria, Jorge, Wildermann, Stefan, Teich, Jurgen
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: ACM 01.11.2018
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ISSN:1558-2434
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Abstract Approximate Computing has emerged as a design paradigm that allows to decrease hardware costs by reducing the accuracy of the computation for applications that are robust against such errors. In Boolean logic approximation, the number of terms and literals of a logic function can be reduced by allowing to produce erroneous outputs for some input combinations. This paper proposes a novel methodology for the approximation of multi-output logic functions. Related work on multi-output logic approximation minimizes each output function separately. In this paper, we show that thereby a huge optimization potential is lost. As a remedy, our methodology considers the effect on all output functions when introducing errors thus exploiting the cross-function minimization potential. Moreover, our approach is integrated into a design space exploration technique to obtain not only a single solution but a Pareto-set of designs with different trade-offs between hardware costs (terms and literals) and error (number of minterms that have been falsified). Experimental results show our technique is very efficient in exploring Pareto-optimal fronts. For some benchmarks, the number of terms could be reduced from an accurate function implementation by up to 15% and literals by up to 19% with degrees of inaccuracy around 0.1% w.r.t. accurate designs. Moreover, we show that the Pareto-fronts obtained by our methodology dominate the results obtained when applying related work.
AbstractList Approximate Computing has emerged as a design paradigm that allows to decrease hardware costs by reducing the accuracy of the computation for applications that are robust against such errors. In Boolean logic approximation, the number of terms and literals of a logic function can be reduced by allowing to produce erroneous outputs for some input combinations. This paper proposes a novel methodology for the approximation of multi-output logic functions. Related work on multi-output logic approximation minimizes each output function separately. In this paper, we show that thereby a huge optimization potential is lost. As a remedy, our methodology considers the effect on all output functions when introducing errors thus exploiting the cross-function minimization potential. Moreover, our approach is integrated into a design space exploration technique to obtain not only a single solution but a Pareto-set of designs with different trade-offs between hardware costs (terms and literals) and error (number of minterms that have been falsified). Experimental results show our technique is very efficient in exploring Pareto-optimal fronts. For some benchmarks, the number of terms could be reduced from an accurate function implementation by up to 15% and literals by up to 19% with degrees of inaccuracy around 0.1% w.r.t. accurate designs. Moreover, we show that the Pareto-fronts obtained by our methodology dominate the results obtained when applying related work.
Author Wildermann, Stefan
Teich, Jurgen
Echavarria, Jorge
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  surname: Teich
  fullname: Teich, Jurgen
  organization: Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, 91058, Germany
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Snippet Approximate Computing has emerged as a design paradigm that allows to decrease hardware costs by reducing the accuracy of the computation for applications that...
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SubjectTerms Approximate computing
Design Space Exploration
Hardware
Logic functions
Logic Simplification
Minimization
Optimization
Space exploration
Title Design Space Exploration of Multi-output Logic Function Approximations
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