TY - GEN
T1 - Many-task applications in the integrated plasma simulator
AU - Foley, Samantha S.
AU - Elwasif, Wael R.
AU - Bernholdt, David E.
AU - Shet, Aniruddha G.
AU - Bramley, Randall
PY - 2010
Y1 - 2010
N2 - This paper discusses the Integrated Plasma Simulator (IPS), a framework for coupled multiphysics simulation of fusion plasmas, in the context of many-task computing. The IPS supports multiple levels of parallelism: individual computational tasks can be parallel, components can launch multiple tasks concurrently, tasks from multiple components can be executed concurrently within a simulation, and multiple simulations can be run simultaneously. Each level of parallelism is constructed on top of the many-task computing capabilities implemented in the IPS, the foundation for the parallelism presented at the multiple simulation level. We show that a modest number of simultaneous simulations, with appropriately sized resource allocations, can provide a better trade-off between resource utilization and overall execution time than if they are run as separate jobs. This approach is highly beneficial for situations in which individual simulation tasks may differ significantly in parallel scalability, as is the case in many scientific communities where coupled simulations rely substantially on legacy code.
AB - This paper discusses the Integrated Plasma Simulator (IPS), a framework for coupled multiphysics simulation of fusion plasmas, in the context of many-task computing. The IPS supports multiple levels of parallelism: individual computational tasks can be parallel, components can launch multiple tasks concurrently, tasks from multiple components can be executed concurrently within a simulation, and multiple simulations can be run simultaneously. Each level of parallelism is constructed on top of the many-task computing capabilities implemented in the IPS, the foundation for the parallelism presented at the multiple simulation level. We show that a modest number of simultaneous simulations, with appropriately sized resource allocations, can provide a better trade-off between resource utilization and overall execution time than if they are run as separate jobs. This approach is highly beneficial for situations in which individual simulation tasks may differ significantly in parallel scalability, as is the case in many scientific communities where coupled simulations rely substantially on legacy code.
KW - Coupled multiphysics simulation
KW - Many-task computing
UR - http://www.scopus.com/inward/record.url?scp=79951849178&partnerID=8YFLogxK
U2 - 10.1109/mtags.2010.5699425
DO - 10.1109/mtags.2010.5699425
M3 - Conference contribution
AN - SCOPUS:79951849178
SN - 9781424497041
T3 - 2010 3rd Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS10
BT - 2010 3rd Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS10
PB - IEEE Computer Society
ER -