从头算分子动力学程序CP2K的性能分析
Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics
摘要：
使用一个现实的分子催化剂系统，我们进行缩放研究的从头算分子动力学模拟使用CP2K代码在英特尔至强CPU和NVIDIA V100 GPU架构。我们探索使用进程放置和亲和力来获得额外的性能改进。我们还使用统计方法来了解性能的变化，尽管在每个分子动力学时间步长的运行时的变化。我们发现CPU运行的理想条件包括每个节点至少有四个MPI等级，每个套接字之间均匀绑定，并且每个核心有一个OpenMP线程，充分利用处理核心，为系统保留核心没有任何好处。只有CPU的模拟扩展到理想的70%或更多，扩展到10个计算节点，之后回报开始更快地减少。与最快的单36核节点仅CPU版本相比，在具有两个NVIDIA V100 GPU的单个40核节点上进行的模拟加速实现了超过3.7倍的加速，并且在我们在五个仅CPU节点上实现的最快时间内显示了13%的加速。
英文摘要：
Using a realistic molecular catalyst system, we conduct scaling studies of ab initio molecular dynamics simulations using the CP2K code on both Intel Xeon CPU and NVIDIA V100 GPU architectures. We explore using process placement and affinity to gain additional performance improvements. We also use statistical methods to understand performance changes in spite of the variability in runtime for each molecular dynamics timestep. We found ideal conditions for CPU runs included at least four MPI ranks per node, bound evenly across each socket, and fully utilizing processing cores with one OpenMP thread per core, no benefit was shown from reserving cores for the system. The CPU-only simulations scaled at 70% or more of the ideal scaling up to 10 compute nodes, after which the returns began to diminish more quickly. Simulations on a single 40-core node with two NVIDIA V100 GPUs for acceleration achieved over 3.7x speedup compared to the fastest single 36-core node CPU-only version, and showed 13% speedup over the fastest time we achieved across five CPU-only nodes.
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