Static Rate-Optimal Scheduling of Iterative Data-Flow Programs Via Optimum Unfolding
IEEE Transactions on Computers
Iterative modulo scheduling: an algorithm for software pipelining loops
MICRO 27 Proceedings of the 27th annual international symposium on Microarchitecture
Efficient formulation for optimal modulo schedulers
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Lifetime-Sensitive Modulo Scheduling in a Production Environment
IEEE Transactions on Computers
Constraint-Based Scheduling
Swing Modulo Scheduling: A Lifetime-Sensitive Approach
PACT '96 Proceedings of the 1996 Conference on Parallel Architectures and Compilation Techniques
Orchestrating the execution of stream programs on multicore platforms
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Embedded Multiprocessors: Scheduling and Synchronization
Embedded Multiprocessors: Scheduling and Synchronization
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Precedence constraint posting for cyclic scheduling problems
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
A constraint based approach to cyclic RCPSP
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
SCAN: a heuristic for near-optimal software pipelining
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
| Hi-index | 0.00 |
This paper proposes a global cumulative constraint for cyclic scheduling problems. In cyclic scheduling a project graph is periodically re-executed on a set of limited capacity resources. The objective is to find an assignment of start times to activities such that the feasible repetition period λ is minimized. Cyclic scheduling is an effective method to maximally exploit available resources by partially overlapping schedule repetitions. In our previous work [4], we have proposed a modular precedence constraint along with its filtering algorithm. The approach was based on the hypothesis that the end times of all activities should be assigned within the period: this allows the use of traditional resource constraints, but may introduce resource inefficiency. The adverse effects are particularly relevant for long activity durations and high resource availability. By relaxing this restriction, the problem becomes much more complicated and specific resource constrained filtering algorithms should be devised. Here, we introduce a global cumulative constraint based on modular arithmetic, that does not require the end times to be within the period. We show the advantages obtained for specific scenarios in terms of solution quality with respect to our previous approach, that was already superior with respect to state of the art techniques.