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Pipelined Iterative Solvers with Kernel Fusion for Graphics Processing Units

机译:具有内核融合功能的流水线迭代求解器,用于图形处理单元

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We revisit the implementation of iterative solvers on discrete graphics processing units and demonstrate the benefit of implementations using extensive kernel fusion for pipelined formulations over conventional implementations of classical formulations. The proposed implementations with both CUDA and OpenCL are freely available in ViennaCL and are shown to be competitive with or even superior to other solver packages for graphics processing units. The highest-performance gains are obtained for small to medium-sized systems, while our implementations are on par with vendor-tuned implementations for very large systems. Our results are especially beneficial for transient problems, where many small to medium-sized systems instead of a single big system need to be solved.
机译:我们重新审视了离散图形处理单元上的迭代求解器的实现,并展示了与传统公式的传统实现相比,将大量内核融合用于流水线公式的实现的好处。用CUDA和OpenCL提出的实施方案可以在ViennaCL中免费获得,并显示出与图形处理单元的其他求解器程序包相比甚至更具竞争优势。对于中小型系统,可以获得最高的性能提升,而对于大型系统,我们的实现与供应商调整的实现相当。我们的结果对于瞬态问题特别有用,在瞬态问题中,需要解决许多中小型系统而不是单个大型系统的问题。

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