A decomposition-based constraint optimization approach for statically scheduling task graphs with communication delays to multiprocessors

We present a decomposition strategy to speed up constraint optimization for a representative multiprocessor scheduling problem. In the manner of Benders decomposition, our technique solves relaxed versions of the problem and iteratively learns constraints to prune the solution space. Typical formula...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Proceedings of the conference on Design, automation and test in Europe s. 57 - 62
Hlavní autori:	Satish, Nadathur, Ravindran, Kaushik, Keutzer, Kurt
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	San Jose, CA, USA EDA Consortium 16.04.2007
Edícia:	ACM Conferences
Predmet:	Computing methodologies Computing methodologies > Artificial intelligence Computing methodologies > Artificial intelligence > Search methodologies Computing methodologies > Artificial intelligence > Search methodologies > Heuristic function construction Theory of computation Theory of computation > Design and analysis of algorithms Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Scheduling algorithms Theory of computation > Design and analysis of algorithms > Online algorithms Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms > Scheduling algorithms Theory of computation > Theory and algorithms for application domains Theory of computation > Theory and algorithms for application domains > Machine learning theory Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning > Sequential decision making
ISBN:	3981080122, 9783981080124
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!