Title
Dynamic Load Balancing Techniques For Particulate Flow Simulations
Abstract
Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is, thus, desirable to minimize these imbalances to reduce the time to solution and to better utilize the available hardware resources. Taking particulate flows as an illustrating example application, we present and evaluate load balancing techniques that tackle this challenging task. This involves a load estimation step in which the currently generated workload is predicted. We describe in detail how such a workload estimator can be developed. In a second step, load distribution strategies like space-filling curves or graph partitioning are applied to dynamically distribute the load among the available processes. To compare and analyze their performance, we employ these techniques to a benchmark scenario and observe a reduction of the load imbalances by almost a factor of four. This results in a decrease of the overall runtime by 14% for space-filling curves.
Year
DOI
Venue
2019
10.3390/computation7010009
COMPUTATION
Keywords
DocType
Volume
high performance computing, multiphysics simulation, lattice Boltzmann method, rigid particle dynamics, particulate flow, load balancing, parallel computing
Journal
7
Issue
ISSN
Citations 
1
2079-3197
0
PageRank 
References 
Authors
0.34
18
2
Name
Order
Citations
PageRank
Christoph Rettinger110.70
Ulrich Rüde250572.00