Advertisement
Published in:
2017 | OriginalPaper | Chapter
Dynamic Load Balancing for Large-Scale Multiphysics Simulations
Authors : Niclas Jansson, Rahul Bale, Keiji Onishi, Makoto Tsubokura
Published in: High-Performance Scientific Computing
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
In parallel computing load balancing is an essential component of any efficient and scalable simulation code. Static data decomposition methods have proven to work well for symmetric workloads. But, in today’s multiphysics simulations, with asymmetric workloads, this imbalance prevents good scalability on future generation of parallel architectures. We present our work on developing a general dynamic load balancing framework for multiphysics simulations on hierarchical Cartesian meshes. Using a weighted dual graph based workload estimation and constrained multilevel graph partitioning, the required runtime for industrial applications could be reduced by 40\(\%\) of the runtime, running on the K computer.