Dynamic Load Balancing Techniques for Particulate Flow Simulations

Journal article

Publication Details

Author(s): Rettinger C, Rüde U
Journal: Computation
Publication year: 2019
Volume: 7
Journal issue: 1
ISSN: 2079-3197


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

FAU Authors / FAU Editors

Rettinger, Christoph
Lehrstuhl für Informatik 10 (Systemsimulation)
Rüde, Ulrich Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)

How to cite

Rettinger, C., & Rüde, U. (2019). Dynamic Load Balancing Techniques for Particulate Flow Simulations. Computation, 7(1). https://dx.doi.org/10.3390/computation7010009

Rettinger, Christoph, and Ulrich Rüde. "Dynamic Load Balancing Techniques for Particulate Flow Simulations." Computation 7.1 (2019).


Last updated on 2019-12-04 at 13:33