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Preconditioned GMRES solver on multiple-GPU architecture

机译:基于多GPU架构的预处理GMRES求解器

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摘要

In 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. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在本文中,我们详细分析了预处理的GMRES算法,并将其分解为要在多GPU架构上实现的组件。向量更新,点积和稀疏矩阵向量乘法(SpMV)的操作是并行实现的。此外,还设计了一种针对SpMV的特定通信机制。预处理器在主机(CPU)上建立,并在设备(GPU)上求解。通过一系列数值实验验证,基于GPU的GMRES求解器有效且获得了良好的并行性能。 (C)2016 Elsevier Ltd.保留所有权利。

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