Skip to main content
Article thumbnail
Location of Repository

A Decomposition-based Constraint Optimization Approach for Statically Scheduling Task Graphs with Communication Delays to Multiprocessors

By Nadathur Satish, Kaushik Ravindran and Kurt Keutzer

Abstract

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 formulations suffer prohibitive run times even on medium-sized problems with less than 30 tasks. Our decomposition strategy enhances constraint optimization to robustly handle instances with over 100 tasks. Moreover, the extensibility of constraint formulations permits realistic application and resource constraints, which is a limitation of common heuristic methods for scheduling. The inherent extensibility, coupled with improved run times from a decomposition strategy, posit constraint optimization as a powerful tool for resource constrained scheduling and multiprocessor design space exploration. 1

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.6597
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://chess.eecs.berkeley.edu... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.