Improved Task Scheduling for Parallel Simulations
Abstract
The objective of this investigation is to design, analyze, and validate the generation of optimal schedules for simulation systems. Improved performance in simulation execution times can greatly improve the return rate of information provided by such simulations resulting in reduced development costs of future computer/electronic systems. Optimal schedule generation of precedence-constrained task systems including iterative feedback systems such as VHDL or war gaming simulations for execution on a parallel computer is known to be N P-hard. Efficiently parallelizing such problems takes full advantage of present computer technology to achieve a significant reduction in the search times required. Unfortunately, the extreme combinatoric 'explosion' of possible task assignments to processors creates an exponential search space prohibitive on any computer for search algorithms which maintain more than one branch of the search graph at any one time. This work develops various parallel modified backtracking (MBT) search algorithms for execution on an iPSC/2 hypercube that bound the space requirements and produce an optimally minimum schedule with linear speed-up. The parallel MBT search algorithm is validated using various feedback task simulation systems which are scheduled for execution on an iPSC/2 hypercube. The search time, size of the enumerated search space, and communications overhead required to ensure efficient utilization during the parallel search process are analyzed. The various applications indicated appreciable improvement in performance using this method.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1991
- Accession Number
- ADA243721
Entities
People
- Andrew E. Mcnear
Organizations
- Air Force Institute of Technology