Processor Allocation and Task Scheduling of Matrix Chain Products on Parallel Systems
IEEE Transactions on Parallel and Distributed Systems
A coarse-grained parallel algorithm for the matrix chain order problem
Proceedings of the 2012 Symposium on High Performance Computing
| Hi-index | 0.00 |
A new technique for obtaining lower bounds on the worst-case time-complexity of optimization problems in the linear decision tree model of computation is presented. This technique is then used to obtain a tight $\Omega(n \log n)$ lower bound for a problem of finding a minimum cost triangulation of a convex polygon with weighted vertices. This problem is similar to the problem of finding an optimal order of computing a matrix chain product. If the lower bound technique could be extended to bounded degree algebraic decision trees, a tight $\Omega(n \log n)$ lower bound for this latter problem would be obtained.