论文标题
量子化学代码CP2K中的基于子矩阵的基于子矩阵的方法
A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CP2K
论文作者
论文摘要
基于密度功能理论（DFT）的电子结构计算是当今HPC工作负载的重要组成部分，并对高性能计算资源提出了很高的需求。要在复杂的大规模系统上执行这些量子机械DFT计算，需要使用所谓的线性缩放方法，而不是常规的立方缩放方法。在这项工作中，我们采用了子序列方法的想法，并将其应用于软件包CP2K中的DFT计算。为此，我们将分布式，大的稀疏矩阵上的基本数字操作转换为局部，较小且近乎密集的矩阵的计算。这使我们能够利用现代CPU的完整浮点性能并利用专用的加速器硬件，在这种硬件之前，性能受到以前的内存带宽的限制。我们展示了实施的功能和性能，并展示了如何通过GPU和FPGA加速它。
Electronic structure calculations based on density-functional theory (DFT) represent a significant part of today's HPC workloads and pose high demands on high-performance computing resources. To perform these quantum-mechanical DFT calculations on complex large-scale systems, so-called linear scaling methods instead of conventional cubic scaling methods are required. In this work, we take up the idea of the submatrix method and apply it to the DFT computations in the software package CP2K. For that purpose, we transform the underlying numeric operations on distributed, large, sparse matrices into computations on local, much smaller and nearly dense matrices. This allows us to exploit the full floating-point performance of modern CPUs and to make use of dedicated accelerator hardware, where performance has been limited by memory bandwidth before. We demonstrate both functionality and performance of our implementation and show how it can be accelerated with GPUs and FPGAs.
