Mixed-Signal Approximate Computation: A Neural Predictor Case Study

Mixed-Signal Approximate Computation: A Neural Predictor Case Study

As transistors shrink and processors trend toward low power, maintaining precise digital behavior grows more expensive. Replacing digital units with analog equivalents sometimes allows similar computation to be performed at higher speed using less power. As a case study in mixed-signal approximate c...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE MICRO 2009-01, Vol.29 (1), p.104-115
Hauptverfasser: St. Amant, R., Jimenez, D.A., Burger, D.
Format: Artikel
Sprache:eng
Schlagworte:
Accuracy
Algorithm design and analysis
Algorithms
Analog circuits
Analog computers
approximate computation
Circuit noise
Computer aided software engineering
Computer architecture
Digital computers
High performance computing
History
imprecise
low power
mixed signal
neural predictor
Prediction algorithms
programmable
Wire
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:As transistors shrink and processors trend toward low power, maintaining precise digital behavior grows more expensive. Replacing digital units with analog equivalents sometimes allows similar computation to be performed at higher speed using less power. As a case study in mixed-signal approximate computation, the authors describe an enhanced neural prediction algorithm and its efficient analog implementation.
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2009.10