基于国产异构计算平台的快速SVD算法及其在海洋资料同化的应用

A Fast SVD Algorithm Based on Domestic Heterogeneous Computing Platform and Its Application in Ocean Data Assimilation

【目的】资料同化已经在大气和海洋的数值预报中发挥重要作用,它可以利用不同来源的观测资料对初始场数据进行修正,从而提高数值预报的准确性,目的在于通过奇异值分解(SVD)算法的改进提高基于国产异构计算平台的资料同化计算效率。【方法】本文在大规模计算环境下并行策略及实现方法基础上,设计并实现了基于国产异构计算平台的CPU和类GPU卡协同批量SVD解算的实现流程和数据结构,并给出了实际性能提升测试数据,同时,完整地使用C/C++实现了资料同化程序。【结果】该算法充分利用国产异构计算平台CPU和计算卡的计算资源,实现了基于SVD的矩阵求逆的高效实现算法,从基础算法上显著提高了资料同化的计算效率。【结论】基于国产异构计算平台CPU和计算卡协同方式的奇异值分解的高效实现算法,其应用可以扩展到量子计算、人工智能、图像处理、信号降噪等领域的算法实现,具有广泛的应用价值,使用C/C++语言的资料同化应用软件,丰富了国产异构计算平台的应用生态。

[Objective]Data assimilation has played an important role in numerical forecasting of the atmosphere and ocean.It can use observation data from different sources to modify initial field data,thereby improving the accuracy of numerical forecasting.The aim is to improve the efficiency of data assimilation calculation based on domestic heterogeneous computing platforms through the improvement of the SVD algorithm.[Methods]This article systematically describes the parallel strategy and implementation method in a large-scale environment,and designs and implements the implementation process and data structure of CPU and GPU-like accelerator collaborative batch SVD solution based on domestic heterogeneous computing platforms.It also provides actual performance improvement test data.At the same time,a complete data assimilation program is implemented using C/C++.[Results]This algorithm fully utilizes the computing resources,CPUs and computing cards of domestic heterogeneous computing platforms,achieving an efficient implementation algorithm for matrix inversion based on singular value decomposition(SVD),and significantly improving the computational efficiency of data assimilation from the basic algorithm.[Conclusions]The efficient implementation algorithm of singular value decomposition based on the collaborative approach of domestic heterogeneous computing platform CPU and computing card can be extended to algorithm implementation in fields such as quantum computing,artificial intelligence,image processing,and signal denoising,etc.It has high application value.The data assimilation application software using C/C++language enriches the application ecosystem of domestic heterogeneous computing platforms.