Task Clustering and Scheduling for Distributed Memory Parallel Architectures
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Benchmarking and comparison of the task graph scheduling algorithms
Journal of Parallel and Distributed Computing
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
A comparison of list schedules for parallel processing systems
Communications of the ACM
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 Parallel and Distributed Systems
DSC: Scheduling Parallel Tasks on an Unbounded Number of Processors
IEEE Transactions on Parallel and Distributed Systems
Decisive Path Scheduling: A New List Scheduling Method
ICPP '97 Proceedings of the international Conference on Parallel Processing
A Realistic Model and an Efficient Heuristic for Scheduling with Heterogeneous Processors
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
A Static Scheduling Heuristic for Heterogeneous Processors
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
A Dynamic Matching and Scheduling Algorithm for Heterogeneous Computing Systems
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Task Scheduling Algorithms for Heterogeneous Processors
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Fast and Effective Task Scheduling in Heterogeneous Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
A Scalable Task Duplication Based Scheduling Algorithm for Heterogeneous Systems
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
A Dynamic Grouping Scheduling for Heterogeneous Internet-Centric Metacomputing System
ICPADS '01 Proceedings of the Eighth International Conference on Parallel and Distributed Systems
Stochastic Scheduling of a Meta-task in Heterogeneous Distributed Computing
ICPPW '01 Proceedings of the 2001 International Conference on Parallel Processing Workshops
Journal of Parallel and Distributed Computing
International Journal of Grid and Utility Computing
A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous processor networks
Journal of Parallel and Distributed Computing
Low power scheduling of DAGs to minimize finish times
HiPC'06 Proceedings of the 13th international conference on High Performance Computing
A New Grid Scheduler with Failure Recovery and Rescheduling Mechanisms: Discussion and Analysis
Journal of Grid Computing
SAPPHIRE: A toolkit for building efficient stream programs for medical video analysis
Computer Methods and Programs in Biomedicine
A path priority-based task scheduling algorithm for heterogeneous distributed systems
International Journal of Communication Networks and Distributed Systems
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In a distributed computing environment, the schedule by which tasks are assigned to processors is critical to minimizing the overall run-time of the application. However, the problem of discovering the schedule that gives the minimum finish time is NP-Complete. This paper addresses static scheduling of a directed a-cyclic task graph (DAG) on a heterogeneous, bounded set of distributed processors to minimize the makespan. By combining several innovative techniques, including insertion-based scheduling and multiple task duplication, we present a new heuristic, known as Heterogeneous N-predecessor Decisive Path (HNDP), for scheduling directed a-cyclic weighted task graphs (DAGs) on a set of heterogeneous processors. We compare the performance of HNDP, under a range of varying input conditions, with two of the best existing heterogeneous heuristics namely HEFT and STDS. The results presented in this paper show that HNDP outperforms the two heuristics in terms of finish time and the number of processors employed over a wide range of parameters. The complexity of HNPD is O(v^2^.p) vs. O(v^2^.p) of HEFT and O(v^2) of STDS where v is the number of nodes in the DAG.