Chen, Zhangxing (John)Yang, B.Liu, Hui2017-03-132017-03-132016-08http://hdl.handle.net/11023/2512http://hdl.handle.net/1880/51849In this paper, we analyze the preconditioned GMRES algorithm in detail and decompose it into components to implement on multiple-GPU architecture. The operations of vector updates, dot products and Sparse Matrix-Vector multiplication (SpMV) are implemented in parallel. In addition, a specific communication mechanism for SpMV is designed. The preconditioner is established on the host (CPU) and solved on the devices (GPUs). Validated by a series of numerical experiments, the GPU-based GMRES solver is effective and favorable parallel performance is achieved.enMathematicsComputer ScienceEngineering-Petroleumjournal articleNSERC: IRC PJ365863-12; AITF: G203000197; AIEES: 3130.10.11575/PRISM/30183