Solving billions of unknowns using the parallel MLFMA and a Tier 1 supercomputer

Algorithmic improvements to the parallel, distributed-memory Multilevel Fast Multipole Algorithm (MLFMA) have resulted in implementations with favorable weak scaling properties. This allows for the simulation of increasingly larger electromagnetic problems, provided that sufficient computational resources are available (B. Michiels et al., “Weak Scalability Analysis of the Distributed-Memory Parallel MLFMA”, IEEE Trans. Antennas Propag., 61(11, 2013). Recently, we were able to benchmark our implementation on the Flemish Supercomputing Centre´s (VSC) Tier 1 supercomputer. This cluster consists of 512 nodes interconnected by an FDR Infiniband network. Each node contains two 8-core Intel Xeon E5-2670 processors and 64 GByte of RAM. The complete system hence provides 8192 CPU cores and 32 TByte of RAM in total.