Computational fluid dynamics (CFD) can serve as a complementary approach to conventional wind tunnel testing to assess the wind flow around tall buildings. Being a clear High Performance Computing (HPC) task, CFD simulations conventionally run on supercomputers and compute clusters using specialized software such as OpenFOAM. The limited availability and high maintenance costs of supercomputers and clusters force small and medium companies to search for the cost-efficient infrastructure to conduct their simulations with the appropriate performance. The on-demand offer of compute capacity by cloud service providers are well suited this task. However, engineers and researchers require extensive expertise and experience in working with cloud computing in order to benefit from running CFD simulations on a cloud.The contribution of the paper to the outlined problem is two-fold: 1) a unique Automated Parallel Processing Application (APPA) tool that hides the cloud management details from the wind engineer and provides an intuitive user interface; 2) the estimation of the optimal number of cores (vCPUs) for virtual machine instances provided by AWS and Google Cloud based on average run time and total cost metrics for a given number of cells of a CFD-simulation. n1-highcpu-96 Google Cloud VM met both goals: low cost and low runtime per timestep. For the number of vCPUs below 16, the c4.8xlarge AWS VM type has the least runtime per timestep in all the cases. Google Cloud instances with high vCPUs are recommended to run the simulations if budget is a big concern.