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Open Access Publications from the University of California

Rapid Aerodynamic Performance Prediction on a Cluster of Graphics Processing Units


Researchers have recently used the new programmable capabilities of the Graphics Processing Unit (GPU) to increase the performance of scientific codes. We investigate the use of a cluster of GPUs for large-scale CFD problems and show order-of-magnitude increases in performance and performance-to-price ratio. We implement two separate compressible flow solvers. First, we develop a CUDA-based solver for the 2D compressible Euler equations and verify the results against a reference multi-block code MBFLO. After demonstrating the performance of our Euler solver, we proceed to develop a new version of MBFLO by adding GPU-accelerated subroutines to the existing Fortran codebase. Using an eight-node cluster equiped with 16 NVIDIA 9800GX2 GPUs, we achieve speedups of up to 496x on our Euler Solver and 88x on MBFLO. This paper describes the numerical, hardware and software techniques that provide significant speedups.

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