This section shows benchmark results using several Amazon EC2 instances for the standard Le Mans race car test case that is part of the STAR-CCM+ benchmark suite. They have all been run using AWS ParallelCluster in the same way as described in this workshop.
It consists of a race car geometry in a single region with a mesh of approximately 17m polyhedral cells. The actual sim file can be obtained from Siemens directly and these particular numbers were taken after running the simulation until 500 iterations and then taking the time from 500 to 600 iterations. This time has been then recalculated as the number of iterations per minute to aid visualization.
All three graphs show the clear improvement from using the network optimized instance; c5n.18xlarge which includes the Elastic Fabric Adapter (EFA). The C5.24xlarge and C5a.24xlarge lose scaling earlier largely because they only have 25Gbit/s of network bandwidth. However it should be noted that the differences are only noticable at lower cells per core, although this is dependant on the problem size and STAR-CCM+ settings e.g solver type.
These graphs are shown per node, per core and cells per core to aid visualization of the results.