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首页> 外文会议>2011 International Conference for High Performance Computing, Networking, Storage and Analysis >Parallelization design on multi-core platforms in density matrix renormalization group toward 2-D Quantum strongly-correlated systems
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Parallelization design on multi-core platforms in density matrix renormalization group toward 2-D Quantum strongly-correlated systems

机译：密度矩阵重归一化组中针对2-D Quantum强相关系统的多核平台上的并行化设计

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摘要

One of the most fascinating issues in modern condensed matter physics is to understand highly-correlated electronic structures and propose their novel device designs toward the reduced carbon-dioxide future. Among various developed numerical approaches for highly-correlated electrons, the density matrix renormalization group (DMRG) has been widely accepted as the most promising numerical scheme compared to Monte Carlo and exact diagonalization in terms of accuracy and accessible system size. In fact, DMRG almost perfectly resolves one-dimensional chain like long quantum systems. In this paper, we suggest its extended approach toward higher-dimensional systems by high-performance computing techniques. The computing target in DMRG is a huge non-uniform sparse matrix diagonalization. In order to efficiently parallelize the part, we implement communication step doubling together with reuse of the mid-point data between the doubled two steps to avoid severe bottleneck of all-to-all communications essential for the diagonalization. The technique is successful even for clusters composed of more than 1000 cores and offers a trustworthy exploration way for two-dimensional highly-correlated systems.
机译：现代凝聚态物理中最引人入胜的问题之一是了解高度相关的电子结构，并为减少二氧化碳的未来提出其新颖的器件设计。在各种高度相关的电子数值方法中，与蒙特卡洛法和精确对角化方法相比，密度矩阵重归一化组（DMRG）已被广泛接受为最有前途的数值方案，其准确性和可访问的系统尺寸都很高。实际上，DMRG几乎可以像长量子系统一样完美地解析一维链。在本文中，我们建议通过高性能计算技术将其扩展为针对高维系统的方法。 DMRG中的计算目标是巨大的非均匀稀疏矩阵对角化。为了有效地并行化零件，我们将通讯步骤加倍，并在两次加倍的步骤之间重用中点数据，以避免对角化必不可少的所有通讯的瓶颈。该技术甚至对于包含1000个以上内核的集群也是成功的，并且为二维高度相关的系统提供了一种值得信赖的探索方式。

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