A Novel Methodology to Optimize High-Performance Computing Hardware for Computational Fluid Dynamics Simulations

We present a novel methodology for the multi-objective optimization of computational fluid dynamics simulations. It is commonly known that Computational Fluid Dynamics (CFD) codes do not scale perfectly with increasing CPU core count. Different hardware types can exhibit qualitatively different scalability that cannot be predicted from hardware specifications, so testing is necessary. Furthermore, we demonstrate performance gains of over 10% by undersubscribing the hardware (that is, using fewer than the available number of CPU cores); testing is necessary to find the optimum undersubscription. Our approach simplifies comparison of alternatives by comparing normalized quantities of speed and cost. Plotting these quantities allows easy and intuitive comparison of alternatives.