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首页> 外文期刊>WSEAS Transactions on Information Science and Applications >Hybrid-Parallel Sparse Matrix-Vector Multiplication and Iterative Linear Solvers with the communication library GPI
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Hybrid-Parallel Sparse Matrix-Vector Multiplication and Iterative Linear Solvers with the communication library GPI

机译:带有通信库GPI的混合并行稀疏矩阵矢量乘法和迭代线性求解器

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摘要

We present a library of Krylov subspace iterative solvers built over the PGAS-type communication layer GPI. The hybrid pattern is here the appropriate choice to reveal the hierarchical parallelism of clusters with multi-and many-core nodes. Our approach includes asynchronous communication and differs in many aspects from the classical one. We first present the GPI-based implementation of the sparse matrix-vector multiplication and then, using as a benchmark the numerical solution of a Poisson boundary value problem in a unit cube, we compare the performance on Intel/Infiniband and CRAY XE6 architectures of our GPI-based Conjugate Gradients and Richardson methods against the ones available in PETSc. The results show good scalability and performance of our approach, at least comparable to these of PETSc.
机译:我们介绍了一个基于PGAS类型的通信层GPI构建的Krylov子空间迭代求解器库。在这里,混合模式是揭示具有多核和多核节点的群集的分层并行性的合适选择。我们的方法包括异步通信,并且在许多方面与经典方法不同。我们首先介绍稀疏矩阵矢量乘法的基于GPI的实现,然后将单位立方体中泊松边界值问题的数值解作为基准,我们比较英特尔/ Infiniband和CRAY XE6体系结构的性能与PETSc中可用的方法相比,基于GPI的共轭梯度法和Richardson方法。结果表明,我们的方法具有良好的可扩展性和性能,至少可与PETSc相比。

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