Multiple-Way Network Partitioning
IEEE Transactions on Computers
Combinatorial algorithms for integrated circuit layout
Combinatorial algorithms for integrated circuit layout
Recent directions in netlist partitioning: a survey
Integration, the VLSI Journal
A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Scheduling Master-Slave Multiprocessor Systems
IEEE Transactions on Computers
Multilevel k-way partitioning scheme for irregular graphs
Journal of Parallel and Distributed Computing
The grid
Hypergraph-Partitioning-Based Decomposition for Parallel Sparse-Matrix Vector Multiplication
IEEE Transactions on Parallel and Distributed Systems
Dynamic mapping of a class of independent tasks onto heterogeneous computing systems
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
The AppLeS parameter sweep template: user-level middleware for the grid
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
GridG: generating realistic computational grids
ACM SIGMETRICS Performance Evaluation Review
Task Execution Time Modeling for Heterogeneous Computing Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Heuristics for Scheduling Parameter Sweep Applications in Grid Environments
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Hybrid Task Scheduling: Integrating Static and Dynamic Heuristics
SBAC-PAD '03 Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
SIAM Journal on Scientific Computing
Permuting Sparse Rectangular Matrices into Block-Diagonal Form
SIAM Journal on Scientific Computing
IEEE Transactions on Parallel and Distributed Systems
A hypergraph partitioning based approach for scheduling of tasks with batch-shared I/O
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Multi-level direct K-way hypergraph partitioning with multiple constraints and fixed vertices
Journal of Parallel and Distributed Computing
Robust resource allocation in a massive multiplayer online gaming environment
Proceedings of the 4th International Conference on Foundations of Digital Games
A novel global harmony search algorithm for task assignment problem
Journal of Systems and Software
Brief paper: An improved differential evolution algorithm for the task assignment problem
Engineering Applications of Artificial Intelligence
Statistical measures for quantifying task and machine heterogeneities
The Journal of Supercomputing
Partitioning Hypergraphs in Scientific Computing Applications through Vertex Separators on Graphs
SIAM Journal on Scientific Computing
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We consider the problem of scheduling an application on a computing system consisting of heterogeneous processors and data repositories. The application consists of a large number of file-sharing otherwise independent tasks. The files initially reside on the repositories. The processors and the repositories are connected through a heterogeneous interconnection network. Our aim is to assign the tasks to the processors, to schedule the file transfers from the repositories, and to schedule the executions of tasks on each processor in such a way that the turnaround time is minimized. We propose a heuristic composed of three phases: initial task assignment, task assignment refinement, and execution ordering. We experimentally compare the proposed heuristics with three well-known heuristics on a large number of problem instances. The proposed heuristic runs considerably faster than the existing heuristics and obtains 10-14% better turnaround times than the best of the three existing heuristics.