[1]王俊超,彭涛,冯光柳. 曙光高性能计算机在数值预报模式中的应用[J].计算机技术与发展,2014,24(10):178-181.
　WANG Jun-chao,PENG Tao,FENG Guang-liu. Application of HPC in Numerical Prediction Model[J].,2014,24(10):178-181.
点击复制

 曙光高性能计算机在数值预报模式中的应用()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年10期
页码:
178-181
栏目:
应用开发研究
出版日期:
2014-10-10

文章信息/Info

Title:
 Application of HPC in Numerical Prediction Model
文章编号:
1673-629X（2014）10-0178-04
作者:
 王俊超; 彭涛; 冯光柳
 中国气象局武汉暴雨研究所 暴雨监测预警湖北省重点实验室
Author(s):
 WANG Jun-chao; PENG Tao; FENG Guang-liu
关键词:
 ; 高性能计算机; 数值预报模式; 并行计算; 加速比
Keywords:
 ; HPC; numerical prediction model; parallel computing; speedup
分类号:
TP39
文献标志码:
A
摘要:
 文中首先介绍了中国气象局武汉暴雨研究所高性能计算机应用现状和目前的模式业务系统，针对气象预报模式精细化对计算能力的更高需求，中国气象局武汉暴雨研究所采用曙光高性能计算机集群对原有集群系统进行升级，升级后的计算节点CPU可提供11.40 TFlops的双精浮点计算能力；其次，讨论了升级后的高性能计算机几个关键技术的现状并对未来进行展望；最后以WRF模式为例，对升级后的高性能计算机的性能进行了分析，得到了较好的加速比。结果表明：新升级的集群系统将大大节省区域高分辨数值预报模式运算时间，有助于提高科研成果的转化效率。
Abstract:
 In this paper,firstly introduce the application of HPC in WHIHR and the current mode of business systems. For the better re-quirements of the weather forecasting model fine to computing ability,the institute of heavy rain of China Meteorological Administration uses the dawn of high-performance computer clusters to upgrade the original cluster system. The upgraded computing node can provide the 11. 40 TFlops double-precision floating-point computing power. Secondly,discuss the present status and the prospect of key technol-ogy of advanced HPC. Finally,taking WRF model as example,analyze the performance of HPC and have a good speedup. The result shows that the new upgraded cluster system would greatly reduce the computation time of regional high-resolution numerical weather pre-diction model. Also it could improve the conversion efficiency of scientific research.

相似文献/References:

[1]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
　ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(10):1.
[2]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
　LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(10):5.
[3]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
　HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(10):13.
[4]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
　HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(10):21.
[5]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
　LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(10):25.
[6]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
　WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(10):29.
[7]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
　LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(10):34.
[8]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
　SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(10):38.
[9]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
　YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(10):43.
[10]余松平[][],蔡志平[],吴建进[],等. GSM-R信令监测选择录音系统设计与实现[J].计算机技术与发展,2014,24(07):47.
　YU Song-ping[][],CAI Zhi-ping[] WU Jian-jin[],GU Feng-zhi[]. Design and Implementation of an Optional Voice Recording System Based on GSM-R Signaling Monitoring[J].,2014,24(10):47.

更新日期/Last Update: 2015-04-03