Cloud computing is an innovative computing paradigm that can potentially bridge the gap between increasing computing demands in computer aided engineering (CAE) applications and limited scalability, flexibility, and agility in traditional computing paradigms. In light of the benefits of cloud computing, high performance computing (HPC) in the cloud has the potential to enable users to not only accelerate computationally expensive CAE simulations (e.g., finite element analysis), but also to reduce costs by utilizing on-demand and scalable cloud computing resources. The objective of this research is to evaluate the performance of running a large finite element simulation in a public cloud. Specifically, an experiment is performed to identify individual and interactive effects of several factors (e.g., CPU core count, memory size, solver computational rate, and input/output rate) on run time using statistical methods. Our experimental results have shown that the performance of HPC in the cloud is sufficient for the application of a large finite element analysis, and that run time can be optimized by properly selecting a configuration of CPU, memory, and interconnect.
