Towards an RCC-Based Accelerator for Computational Fluid Dynamics Applications

摘要

Computational Fluid Dynamics (CFD) applications are a critical tool in designing sophisticated mechanical systems such as jet engines and gas turbines. CFD applications use intensive floating-point calculations and are typically run on High-Performance Computing (HPC) systems. We analyze three of the most compute intensive functions (Euler, Viscous, and Smoothing algorithms) and develop a baseline system architecture for accelerating these functions in RCC hardware. We then present detailed design data for the most compute intensive (Euler) function. Based on this analysis, we show that an RCC-based CFD accelerator—compared to conventional processors—promises dramatic improvement in sustained compute speed at better price-performance ratios coupled with much lower overall power consumption.