Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
Resource-constrained loop list scheduler for DSP algorithms
Journal of VLSI Signal Processing Systems - Special issue on VLSI design methodologies for digital signal processing systems
Achieving Full Parallelism Using Multidimensional Retiming
IEEE Transactions on Parallel and Distributed Systems
Task assignment and transaction clustering heuristics for distributed systems
Information Sciences: an International Journal - Special issue: load balancing in distributed systems
Adaptively Scheduling Parallel Loops in Distributed Shared-Memory Systems
IEEE Transactions on Parallel and Distributed Systems
Communication-minimal tiling of uniform dependence loops
Journal of Parallel and Distributed Computing
Space-efficient scheduling of nested parallelism
ACM Transactions on Programming Languages and Systems (TOPLAS)
Probabilistic Loop Scheduling for Applications with Uncertain Execution Time
IEEE Transactions on Computers
Optimizing Overall Loop Schedules Using Prefetching and Partitioning
IEEE Transactions on Parallel and Distributed Systems
A simple proof technique for priority-scheduled systems
Information Processing Letters - Special issue in honor of Edsger W. Dijkstra
Optimal Distribuion of Loops containing no Dependence Cycles
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
Probabilistic Loop Scheduling Considering Communication Overhead
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Feedback Guided Dynamic Loop Scheduling: Algorithms and Experiments
Euro-Par '98 Proceedings of the 4th International Euro-Par Conference on Parallel Processing
Communication-sensitive loop scheduling for DSP applications
IEEE Transactions on Signal Processing
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Many approaches have been described for the parallel loop scheduling problem for shared-memory systems, but little work has been done on the data-dependent loop scheduling problem (nested loops with loop carried dependencies). In this paper, we propose a general model for the data-dependent loop scheduling problem on distributed as well as shared memory systems. In order to achieve load balancing and low runtime scheduling and communication overhead, our model is based on a loop task graph and the notion of critical path. In addition, we develop a heuristic algorithm based on our model and on genetic algorithms to test the reliability of the model. We test our approach on different scenarios and benchmarks. The results are very encouraging and suggest a future parallel compiler implementation based on our model.