A recursive technique for computing lower-bound performance of schedules
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Estimation of lower bounds in scheduling algorithms for high-level synthesis
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Automata-Based Symbolic Scheduling for Looping DFGs
IEEE Transactions on Computers
A fast approach to computing exact solutions to the resource-constrained scheduling problem
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Algorithmic and Register-Transfer Level Synthesis: The System Architect's Workbench
Algorithmic and Register-Transfer Level Synthesis: The System Architect's Workbench
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
The Art of Computer Programming, Volume 4, Fascicle 4: Generating All Trees--History of Combinatorial Generation (Art of Computer Programming)
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
| Hi-index | 0.00 |
We propose an in-place search algorithm for computing the exact solutions to the resource constrained scheduling problem. This algorithm supports operation chaining, pipelining and multicycling in the underlying scheduling problem. Based on two lower-bound estimation mechanisms that are capable of predicting the criterion values of search nodes represented by partially scheduled data flow graphs, the proposed algorithm can effectively prune the nonpromising search space and finds the optimum usually several times faster than existing techniques. As opposed to existing search-based scheduling techniques whose space complexity is squared or exponential in the search depth, our approach requires only a constant storage space during the traversal of the search tree. The low space complexity is accomplished by using a combination-generating algorithm, which leads our approach to visit search nodes in such a way that each one is obtained by making only a small change to its sibling without keeping any parent nodes in memory. Experimental results on several well known benchmarks with varying resource constraints show the effectiveness of the proposed algorithm.