Energy Efficiency through Significance-Based Computing

Energy Efficiency through Significance-Based Computing

An extension of approximate computing, significance-based computing exploits applications' inherent error resiliency and offers a new structural paradigm that strategically relaxes full computational precision to provide significant energy savings with minimal performance degradation.

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Bibliographische Detailangaben
Veröffentlicht in:Computer (Long Beach, Calif.) Calif.), 2014-07, Vol.47 (7), p.82-85
Hauptverfasser: Nikolopoulos, Dimitrios S., Vandierendonck, Hans, Bellas, Nikolaos, Antonopoulos, Christos D., Lalis, Spyros, Karakonstantis, Georgios, Burg, Andreas, Naumann, Uwe
Format: Artikel
Sprache:eng
Schlagworte:
Algorithm design and analysis
Algorithmics. Computability. Computer arithmetics
Applied sciences
approximate computing
Approximation
automatic differentiation
Circuit faults
Computation
Computer science
control theory
systems
Computers
Convergence
Educational institutions
Energy conservation
Energy efficiency
Energy management
energy wall
Errors
Exact sciences and technology
Green computing
Hardware
iterative solvers
on-chip power consumption
Optimization
Performance degradation
Reliability
SCoRPiO
significance-based computing
Significance-Based Computing for Reliability and Power Optimization
Software engineering
Theoretical computing
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Beschreibung
Zusammenfassung:An extension of approximate computing, significance-based computing exploits applications' inherent error resiliency and offers a new structural paradigm that strategically relaxes full computational precision to provide significant energy savings with minimal performance degradation.
ISSN:0018-9162
1558-0814
DOI:10.1109/MC.2014.182