Approximate Computing (AC) waives error free computation to improve circuits performances. Adaptive Least-Mean-Squares (LMS) filters can benefit from AC, being both power hungry and inherently approximate. In this paper an approximate LMS filter is proposed, which is able to change, at runtime, the precision level by acting on an external quality knob. An auxiliary circuit enables the approximation mode, in which the update of some of the filter coefficients is frozen. The proposed filter achieves a power improvement in the range 5–32%, as function of the tolerable quality degradation.
Design of low-power approximate LMS filters with precision-scalability / Esposito, D.; Di Meo, G.; De Caro, D.; Strollo, A. G. M.; Napoli, E.. - 550:9783030119720(2019), pp. 237-243. (Intervento presentato al convegno International Conference on Applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2018 tenutosi a ita nel 2018) [10.1007/978-3-030-11973-7_27].
Design of low-power approximate LMS filters with precision-scalability
Esposito D.;Di Meo G.;De Caro D.;Strollo A. G. M.;Napoli E.
2019
Abstract
Approximate Computing (AC) waives error free computation to improve circuits performances. Adaptive Least-Mean-Squares (LMS) filters can benefit from AC, being both power hungry and inherently approximate. In this paper an approximate LMS filter is proposed, which is able to change, at runtime, the precision level by acting on an external quality knob. An auxiliary circuit enables the approximation mode, in which the update of some of the filter coefficients is frozen. The proposed filter achieves a power improvement in the range 5–32%, as function of the tolerable quality degradation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
