Multi-criteria partitioning of multi-block structured grids
Hengjie Wang, Aparna M. Chandramowlishwaran · 2019
Partitioning of multi-block structured grids impacts the performance and scalability of numerical simulations. An optimal partitioner should achieve both load balance and minimize communication time. The state-of-art domain decomposition algorithms do a good job at balancing the load across processors. However, even if the work is well balanced, the communication cost might not be. The two main factors that impact communication cost are edge cuts and communication volume. The current partitioners primarily focus on reducing the total communication volume and rely on simple techniques such as cutting at the longest edge which does not capture the connectivity in the geometry. They also don't factor the effect of the network's latency and bandwidth for partitioning resulting in the same partition across all platforms. In addition, their performance tests mostly adopt a flat MPI model where the partition's effect on communication is hidden by the fast shared memory accesses between cores on the same node.