Abstract
We are focusing on an iterative solver for the three-dimensional Helmholtz equation on multi-GPU using CUDA (Compute Unified Device Architecture). The Helmholtz equation discretized by a second order finite difference scheme is solved with Bi-CGSTAB preconditioned by a shifted Laplace multigrid method. Two multi-GPU approaches are considered: data parallelism and split of the algorithm. Their implementations on multi-GPU architecture are compared to a multi-threaded CPU and single GPU implementation. The results show that the data parallel implementation is suffering from communication between GPUs and CPU, but is still a number of times faster compared to many-cores. The split of the algorithm across GPUs limits communication and delivers speedups comparable to a single GPU implementation.
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