Lattice QCD with Domain Decomposition on Intel® Xeon Phi Co-Processors

New Orleans, LA(2014)

引用 49|浏览47
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摘要
The gap between the cost of moving data and the cost of computing continues to grow, making it ever harder to design iterative solvers on extreme-scale architectures. This problem can be alleviated by alternative algorithms that reduce the amount of data movement. We investigate this in the context of Lattice Quantum Chromodynamics and implement such an alternative solver algorithm, based on domain decomposition, on Intel® Xeon Phi™ co-processor (KNC) clusters. We demonstrate close-to-linear on-chip scaling to all 60 cores of the KNC. With a mix of single- and half-precision the domain-decomposition method sustains 400-500 Gflop/s per chip. Compared to an optimized KNC implementation of a standard solver [1], our full multi-node domain-decomposition solver strong-scales to more nodes and reduces the time-to-solution by a factor of 5.
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关键词
coprocessors,data handling,iterative methods,lattice theory,multiprocessing systems,physics computing,quantum chromodynamics,Intel Xeon Phi coprocessors,KNC cluster,alternative solver algorithm,close-to-linear on-chip scaling,data movement,domain decomposition,extreme-scale architecture,iterative solvers,lattice QCD,lattice quantum chromodynamics,multinode domain-decomposition solver,Domain decomposition,G.1.3 [Numerical Analysis]: Numerical Linear Algebra Sparse,Intel® Xeon Phi coprocessor,Lattice QCD Categories and subject descriptors: D.3.4 [Programming Languages]: Processors Optimization,and very la,structured
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