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

S. Heybrock, B. Joó, Dhiraj D. Kalamkar, M. Smelyanskiy, K. Vaidyanathan, T. Wettig, P. Dubey
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引用次数: 36

Abstract

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 Chromo dynamics 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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基于Intel®Xeon Phi协处理器的点阵QCD域分解
移动数据的成本和计算成本之间的差距继续扩大,这使得在极端规模架构上设计迭代求解器变得更加困难。这个问题可以通过减少数据移动量的替代算法得到缓解。我们在晶格量子Chromo动力学的背景下研究了这一点,并在Intel®Xeon Phi协处理器(KNC)集群上实现了基于域分解的替代求解器算法。我们展示了接近线性的片上扩展到KNC的所有60个内核。在单精度和半精度的混合下,域分解方法每个芯片维持400-500 Gflop/s。与标准求解器的优化KNC实现[1]相比,我们的完整多节点域分解求解器强缩放到更多节点,并将求解时间减少了5倍。
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