Design of MILC Lattice QCD Application for GPU Clusters

Guochun Shi, S. Gottlieb, A. Torok, V. Kindratenko
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引用次数: 14

Abstract

We present an implementation of the improved staggered quark action lattice QCD computation designed for execution on a GPU cluster. The parallelization strategy is based on dividing the space-time lattice along the time dimension and distributing the sub-lattices among the GPU cluster nodes. We provide a mixed-precision floating-point GPU implementation of the multi-mass conjugate gradient solver. Our single GPU implementation of the conjugate gradient solver achieves a 9x performance improvement over the highly optimized code executed on a state-of-the-art eight-core CPU node. The overall application executes almost six times faster on a GPU-enabled cluster vs. a conventional multi-core cluster. The developed code is currently used for running production QCD calculations with electromagnetic corrections.
GPU集群中MILC点阵QCD应用的设计
我们提出了一种改进的交错夸克作用晶格QCD计算的实现,设计用于在GPU集群上执行。该并行化策略基于沿时间维度划分时空格,并将子格分布在GPU集群节点之间。我们提供了一个混合精度浮点GPU实现的多质量共轭梯度求解器。我们的共轭梯度求解器的单个GPU实现实现了在最先进的八核CPU节点上执行的高度优化代码的9倍性能改进。在支持gpu的集群上,整个应用程序的执行速度几乎是传统多核集群的六倍。开发的代码目前用于运行具有电磁校正的生产QCD计算。
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