When designing an approximate computing system, the selection of the resources to modify is key. It is important that the error introduced in the system remains reasonable, but the size of the design exploration space can make this extremely difficult. In this paper, we propose to exploit a new metric for this selection: data lifetime. The concept comes from the field of reliability, where it can guide selective hardening: the more often a resource handles "live" data, the more critical it be-comes, the more important it will be to protect it. In this paper, we propose to use this same metric in a new way: identify the less critical resources as approximation targets in order to minimize the impact on the global system behavior and there-fore decrease the impact of approximation while increasing gains on other criteria.

Approximate computing design exploration through data lifetime metrics / Savino, A.; Portolan, Michele; Leveugle, R.; Di Carlo, S.. - ELETTRONICO. - (2019), pp. 1-7. (Intervento presentato al convegno 24th IEEE European Test Symposium (ETS 2019) tenutosi a Baden Baden, D nel May 27-31 2019) [10.1109/ETS.2019.8791523].

Approximate computing design exploration through data lifetime metrics

Savino A.;PORTOLAN, MICHELE;Di Carlo S.
2019

Abstract

When designing an approximate computing system, the selection of the resources to modify is key. It is important that the error introduced in the system remains reasonable, but the size of the design exploration space can make this extremely difficult. In this paper, we propose to exploit a new metric for this selection: data lifetime. The concept comes from the field of reliability, where it can guide selective hardening: the more often a resource handles "live" data, the more critical it be-comes, the more important it will be to protect it. In this paper, we propose to use this same metric in a new way: identify the less critical resources as approximation targets in order to minimize the impact on the global system behavior and there-fore decrease the impact of approximation while increasing gains on other criteria.
2019
978-1-7281-1173-5
File in questo prodotto:
File Dimensione Formato  
ETS19_CAMERAREADY_V1.2.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 356.58 kB
Formato Adobe PDF
356.58 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2751349
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo