Scheduling precedence graphs in systems with interprocessor communication times
SIAM Journal on Computing
Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
Performance of dynamic load balancing algorithms for unstructured mesh calculations
Concurrency: Practice and Experience
Parallel dynamic graph partitioning for adaptive unstructured meshes
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
Benchmarking and comparison of the task graph scheduling algorithms
Journal of Parallel and Distributed Computing
Computing in Science and Engineering
The Art of Molecular Dynamics Simulation
The Art of Molecular Dynamics Simulation
Simulation for the Social Scientist
Simulation for the Social Scientist
Parallel Individual-Based Modeling of Everglades Deer Ecology
IEEE Computational Science & Engineering
IEEE Transactions on Parallel and Distributed Systems
Modeling Dynamic Load Balancing in Molecular Dynamics to Achieve Scalable Parallel Execution
IRREGULAR '98 Proceedings of the 5th International Symposium on Solving Irregularly Structured Problems in Parallel
Scheduling Distributed Applications: the SimGrid Simulation Framework
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Performance Modeling for Entity-Level Simulations
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Task mapping and remapping strategies for parallel entity-level simulations
Task mapping and remapping strategies for parallel entity-level simulations
| Hi-index | 0.00 |
Scientists have long relied on abstract models to study phenomena that are too complex for direct observation and experimentation. As new scientific modeling methodologies emerge, new computing technologies must be developed. In this paper, we focus on entity-level modeling, a modeling approach that is gaining prevalence in many scientific fields. Although the principles of entity-level modeling are straightforward, entity-level simulations require a large amount of compute resource and grid platforms can meet such resource needs. Unfortunately, efficient large-scale distributed entity-level simulations have proven elusive, typically due to non-determinism that renders classical distributed application deployment strategies ineffective. In this work, we propose a method for dynamically remapping application tasks to cope with this inherent non-determinism. We evaluate the efficacy of this method in a simulated grid computing environment and discuss the feasibility of executing entity-level applications on grids.