Abstract
The advances in multi-core architecture for general-purpose computing in the past decade have tremendously increased the available raw computing power. The two major architectures are the central processing unit (CPU) and the graphics processing unit (GPU). GPUs have been developed recently as general purpose processors. The present work is focused on the performance of unstructured CFD solvers on the GPU. For this purpose an explicit and implicit solvers were developed. The explicit solver for the GPU and the multicore CPU were generated using the OPlus 2 library. This was achieved by implementing minimal extensions to the sequential code. The explicit solver achieved a speedup of an order of magnitude on the GPU, compared to the multi-core CPU code. For the explicit solver the GPU is a cost effective option compared to the CPU. On the other hand, the implicit solver using the Jacobi linear solver was implemented in two variants. The first using the OPlus 2 library and the second using NVIDIA library. The manufacturer library performed better than the OPlus 2 implementation. This was due to the inefficient implementation of the OPlus 2 version. The NVIDIA library gave a speedup of 27x compared to the sequential version. Hence, for the implicit solver the GPU might not be a viable option.