天气雷达网资料拼图方法研究

天气雷达组网拼图,是克服单部雷达探测范围有限,发挥多部雷达相互辅助大范围监测灾害性天气的有效手段。本文在分析现有天气雷达组网拼图方法和存在问题的基础上,对天气雷达组网拼图的资料网格化、重叠区域处理、资料投影等方面作了进一步研究。对雷达反射率因子网格化问题,对比分析了Barnes和双线性插值算法的特性,说明Barnes插值算法网格化资料平滑且能较好地保存雷达资料特征;在重叠区域的资料订正方面,采用概率分布方法,实现了对雷达资料作用距离和天线指北等系统误差的订正,结果表明订正后的资料在重叠区域中各雷达资料的吻合度得到了加强;最后采用兰勃特投影法将天气雷达组网拼图投影到统一底图中。     

天气雷达组网拼图并行处理方法研究

天气雷达组网拼图并行处理的目的就是为了满足实时业务的需求,通常的串性方法在雷达运行的六分钟周期内不能完成。利用共享存储多核处理器的高性能服务器,研发了高频度实时全国天气雷达资料处理的并行计算系统,根据单部天气雷达处理和多部雷达拼图的特点,提出了进程级别和线程级别细粒度的OpenMP共享内存编程的两级并行方法,给出一个合理的派生线程粒度数,同时利用共享内存文件的方法提高程序的执行效率。实验结果表明,使用两级的并行计算等方法可以满足全国天气雷达实时处理的要求。利用并行计算实现实时性要求高的业务系统是重要的手段。     

天气雷达组网拼图并行处理方法研究

天气雷达组网拼图并行处理的目的就是为了满足实时业务的需求,通常的串性方法在雷达运行的六分钟周期内不能完成.利用共享存储多核处理器的高性能服务器,研发了高频度实时全国天气雷达资料处理的并行计算系统,根据单部天气雷达处理和多部雷达拼图的特点,提出了进程级别和线程级别细粒度的OpenMP共享内存编程的两级并行方法,给出一个合理的派生线程粒度数,同时利用共享内存文件的方法提高程序的执行效率.实验结果表明,使用两级的并行计算等方法可以满足全国天气雷达实时处理的要求.利用并行计算实现实时性要求高的业务系统是重要的手段.     

多普勒天气雷达数据插值方法比较研究

天气雷达资料插值处理是对天气雷达获取的资料做综合分析以及进一步的处理必要前提,也是天气雷达组网拼图和三维显示的重要基础.本文主要研究了四种天气雷达资料的插值方法,并对其插值效果进行了比较分析,结果发现,自适应Barnes插值法是一种较为有效的插值方法,能够较好地保留原始资料中回波反射率的结构特征,并且能够得到比较连续的回波反射率三维分析数据场.     

长三角地区雷达同步观测组网拼图技术研究及实现

针对短时临近天气预报对多普勒天气雷达资料的高实时性要求,基于雷达组网同步观测、基数据采集和实时传输技术支持,设计研发了长三角地区12部雷达的三维组网拼图系统。系统运行稳定可靠,拼图时效提高20分钟以上。     

基于GIS技术和天气雷达的短临预警平台研究

天气雷达和自动气象站资料分析应用是短临天气监测预警的重要内容。以VB6.0为开发平台,利用ArcEngine的GIS组件技术,通过对多普勒雷达资料的网格化处理及其在GIS地图中的反演,将自动站实时资料作为属性数据在GIS地图中显示和分析,建立短临预警平台。该平台实现了在GIS下雷达资料、自动站实况、预警信号的动态监控功能,并自动发布手机预警信息,具备了较强的决策预警能力,有助于提高气象台站对突发灾害性天气的短时临近预警水平。     

建三江平原C波段雷达回波强度一致性定标与分析

本文基于相关系数法,以建三江与佳木斯两部新一代天气雷达为例,对两部雷达定标前后天气过程基数据进行解析,通过典型天气过程中两部雷达扫描重合地区回波概率密度、网格化散点图、强度分布图等多种图形图表进行回归统计分析,验证基于数理统计的相关系数法,对依据雷达气象方程的回波强度定标具有良好的指导效果.     

多普勒天气雷达二次产品处理系统的设计

多普勒天气雷达是目前检测中小尺度灾害性天气最有效、最先进的手段之一.为了满足业务和科研对雷达资料处理的需求,将科研成果转化为业务应用,提高观测资料的处理能力,本文基于模块化编程和动态模块嵌入等技术设计和实现了雷达二次产品处理系统.该系统集原始数据处理、反演和绘图显示功能于一体,兼容多种数据格式,产品丰富,并支持模块定制,具有良好的兼容性和较强的扩展能力;在界面设计上,充分考虑到用户的多元化,方便各级用户的操作使用,界面友好.     

利用VB实现雷达图片资料数字化的做法

气象雷达在日常预报中发挥着越来越重要的作用,特别是短时预警、中、小尺度天气系统(如台风和暴雨云系)。气象雷达建设的成本比较大,对于没有安装雷达的气象站,只能使用经过合成后的雷达图片资料。若预报人员想利用雷达资料进行再利用,只有雷达图片资料就比较麻烦。由于本站实际应用需要,利用Photoshop图片处理工具获得雷达图基本信息,然后利用VB高级编程语言对图像素点的RGB进行提取后分析,从而实现了雷达图片资料数字化。     

新一代天气雷达原始资料数据库设计

随着我国新一代天气雷达布网工作的展开,将逐步积累起大量的天气雷达原始资料。为充分高效的利用这些可能达到海量存储量级的资料开发一个适应气象部门特殊需要的雷达资料数据库是一项极有意义的工作。本文利用VisualFoxPro6.0设计的新一代天气雷达原始资料数据库,除具有一般数据库的基本功能外,还可以将不同厂家生产的不同类型的雷达数据入库,同时针对不同的天气类型进行分类资料查询,为气象科研工作者提供方便。     

Legacy code and parallel computing: updating and parallelizing a numerical model

In this paper, we present several important details in the process of legacy code parallelization, mostly related to the problem of maintaining numerical output of a legacy code while obtaining a balanced workload for parallel processing. Since we maintained the non-uniform mesh imposed by the original finite element code, we have to develop a specially designed data distribution among processors so that data restrictions are met in the finite element method. In particular, we introduce a data distribution method that is initially used in shared memory parallel processing and obtain better performance than the previous parallel program version. Besides, this method can be extended to other parallel platforms such as distributed memory parallel computers. We present results including several problems related to performance profiling on different (development and production) parallel platforms. The use of new and old parallel computing architectures leads to different behavior of the same code, which in all cases provides better performance in multiprocessor hardware.

     

宿主机和并行处理机共享存储器模板的设计与实现

本文介绍了宿主机和并行处理机（MPP）之间采用共享存储器模板的数据交换方式,设计并实现了具有一定通用性的共享存储器模板。该模板采用主从式总线切换控制方法,存储器的组织方式可变,能够提供不同的访问带宽,可以为不同的宿主机和协处理机系统提供数据共享。     

Coarse grained gather and scatter operations with applications

We introduce asymptotically optimal algorithms for gathering and scattering a small-to-moderate sized set of data on a coarse grained parallel computer. We use these operations to obtain efficient to optimal solutions to several fundamental problems in image processing and string matching (exact or approximate) for coarse grained parallel computers.     

Implementation and performance of a parallel version of the HIRLAM limited area atmospheric model

The HIRLAM (high resolution limited area modelling) limited-area atmospheric model was originally developed and optimized for shared memory vector-based computers, and has been used for operational weather forecasting on such machines for several years. This paper describes the algorithms applied to obtain a highly parallel implementation of the model, suitable for distributed memory machines. The performance results presented indicate that the parallelization effort has been successful, and the Norwegian Meteorological Institute will run the parallel version in production on a Cray T3E.     

BaLinda Lisp: Design and implementation

BaLinda Lisp is a parallel Lisp dialect employing a shared memory model of parallel processing together with a subset of the Linda tuple space operators. Also included in the design is speculative processing. The aim is to have shared memory multiprocessing with the tuple space acting as the main data structure through which synchronization is done. The result is a flexible programming language. In this paper, we shall describe the design philosophy of BaLinda Lisp, discuss its implementation on three multiprocessing platforms, give examples of programs written in BaLinda Lisp and discuss future work on the language.     

主从式MPP并行计算机系统设计方案研究

根据航天实时图象处理的需求,本文设计了一种基于MPP技术的主从式并行计算机系统,主要介绍主从机通过共享数据存储器的通信方式和互斥工作方式。遵从实时性、可靠性、高精度原则,该系统采用了程序和数据分开存储的组织结构。     

A new parallel sorting approach with sorting memory module

A new approach to accelerating parallel sorting processes is introduced in this paper. This approach involves the design of a new type of memory chip with sorting functions. This type of sorting memory chip is feasible with today's VLSI techniques. A memory module organizing several sorting memory chips associated with additional ECL or TTL control logic circuits is also presented. Using the sorting memory modules in a shared memory parallel processor machine, parallel sorting algorithms such as the column sort method can reduce the row access time significantly and avoid data collisions in the interconnection network. Experimental simulation results on the practical speedup achieved and the memory utilization for the proposed approach are described.     

Efficient parallel implementation of a density peaks clustering algorithm on graphics processing unit

The density peak (DP) algorithm has been widely used in scientific research due to its novel and effective peak density-based clustering approach. However, the DP algorithm uses each pair of data points several times when determining cluster centers, yielding high computational complexity. In this paper, we focus on accelerating the time-consuming density peaks algorithm with a graphics processing unit (GPU). We analyze the principle of the algorithm to locate its computational bottlenecks, and evaluate its potential for parallelism. In light of our analysis, we propose an efficient parallel DP algorithm targeting on a GPU architecture and implement this parallel method with compute unified device architecture (CUDA), called the ‘CUDA-DP platform’. Specifically, we use shared memory to improve data locality, which reduces the amount of global memory access. To exploit the coalescing accessing mechanism of GPU, we convert the data structure of the CUDA-DP program from array of structures to structure of arrays. In addition, we introduce a binary search-and-sampling method to avoid sorting a large array. The results of the experiment show that CUDA-DP can achieve a 45-fold acceleration when compared to the central processing unit based density peaks implementation.     

TreadMarks: shared memory computing on networks of workstations

Shared memory facilitates the transition from sequential to parallel processing. Since most data structures can be retained, simply adding synchronization achieves correct, efficient programs for many applications. We discuss our experience with parallel computing on networks of workstations using the TreadMarks distributed shared memory system. DSM allows processes to assume a globally shared virtual memory even though they execute on nodes that do not physically share memory. We illustrate a DSM system consisting of N networked workstations, each with its own memory. The DSM software provides the abstraction of a globally shared memory, in which each processor can access any data item without the programmer having to worry about where the data is or how to obtain its value     

GRAPES动力框架中大规模稀疏线性系统并行求解及优化

赫姆霍兹方程求解是GRAPES数值天气预报系统动力框架中的核心部分,可转换为大规模稀疏线性系统的求解问题,但受限于硬件资源和数据规模,其求解效率成为限制系统计算性能提升的瓶颈。分别通过MPI、MPI+OpenMP、CUDA三种并行方式实现求解大规模稀疏线性方程组的广义共轭余差法,并利用不完全分解LU预处理子（ILU）优化系数矩阵的条件数,加快迭代法收敛。在CPU并行方案中,MPI负责进程间粗粒度并行和通信,OpenMP结合共享内存实现进程内部的细粒度并行,而在GPU并行方案中,CUDA模型采用数据传输、访存合并及共享存储器方面的优化措施。实验结果表明,通过预处理优化减少迭代次数对计算性能提升明显,MPI+OpenMP混合并行优化较MPI并行优化性能提高约35%,CUDA并行优化较MPI+OpenMP混合并行优化性能提高约50%,优化性能最佳。