Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Efficient Local Search for DAG Scheduling
IEEE Transactions on Parallel and Distributed Systems
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Low-Cost Task Scheduling for Distributed-Memory Machines
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Knowledge and Data Engineering
Local Search for DAG Scheduling and Task Assignment
ICPP '97 Proceedings of the international Conference on Parallel Processing
Decisive Path Scheduling: A New List Scheduling Method
ICPP '97 Proceedings of the international Conference on Parallel Processing
Mapping and Scheduling for Architecture Exploration of Networking SoCs
VLSID '03 Proceedings of the 16th International Conference on VLSI Design
Dynamic Task Scheduling with Security Awareness in Real-Time Systems
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 15 - Volume 16
CODES+ISSS '07 Proceedings of the 5th IEEE/ACM international conference on Hardware/software codesign and system synthesis
Expert Systems with Applications: An International Journal
Real-time scheduling with quality of security constraints
International Journal of High Performance Computing and Networking
Multi-constraint system scheduling using dynamic and delay ant colony system
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
A task remapping technique for reliable multi-core embedded systems
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
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Abstract: The DAG scheduling problem is a rich land of research and a plethora of algorithms for solving this problem have been reported in the literature. However, designing a scheduling algorithm of low complexity without sacrificing performance remains a challenging obstacle from a practical perspective. In this paper, we present a local search-based scheduling algorithm that attempts to meet this challenge. The proposed algorithm is called Fast Assignment using Search Technique (FAST). Its overall time complexity is only O(e) where e is the number of edges in the DAG. The algorithm works by first generating an initial solution and then refining it using local neighborhood search. The algorithm outperforms numerous previous algorithms while taking dramatically smaller execution times. The distinctive feature of our research is that the performance evaluation is not carried out using simulation, rather we have tested our proposed algorithm and compared it with other algorithms using a parallel compiler with real applications on the Intel Paragon.