【作者】 李兴盛；

【导师】 刘素芹；

【作者基本信息】 中国石油大学 ， 计算机科学与技术， 2010， 硕士

【摘要】 石油地震资料处理需要海量存储和巨量计算,一直是高性能计算的重要应用领域。基于Linux的集群计算机系统由于在性价比、可靠性和可扩展性方面的明显优势,已成为目前地震资料处理的主流平台。对地震资料处理PC集群的并行效率进行研究,可以充分利用现有的软硬件资源,提高地震资料处理集群的整体效能,提高地质效果和经济效益,具有重要的实际意义。本文在分析地震资料处理系统的特点的基础上,找出了影响地震资料处理PC集群并行效率的关键因素,主要是I/O瓶颈问题和串行程序在并行环境中的低运行效率。为了解决上述问题,本文主要从并行文件系统和并行编程两方面开展研究工作。本文首先利用普通PC机和MPI技术构建了一个PC集群,对其进行了LINPACK基准测试,分析了影响集群性能的几个关键因素并提出了相关建议。为了解决地震资料处理集群中日益严重的I/O瓶颈问题,本文在研究并行文件系统理论的基础上,将Lustre并行文件系统部署到了实验集群中,利用iozone对NFS和Lustre进行了对比测试。结果表明,Lustre能够更好地适应并发I/O的要求,可有效缓解I/O瓶颈问题。为了提高Lustre的安全性,本文设计了一个基于PKI的Lustre安全模型。在研究相关并行程序设计和开发理论的基础上,对地震资料处理软件中的核心算法快速傅里叶变换和矩阵乘法操作,利用MPI、OpenMP和CUDA等技术进行了并行化,并与相关串行程序在执行耗时方面进行了比较。测试结果表明,通过对计算密集型算法进行并行化,可以明显缩短程序运行周期。将Lustre并行文件系统和并行编程技术应用到实际地震资料处理系统,通过对实际地震资料的处理测试表明,Lustre和并行编程技术可以显著缩短地震资料处理周期,提高程序运行效率。此外,本文还研究了编译器、运行环境、数学库等因素对程序效率的影响,得到了一些有意义的结论,并对进一步提高并行效率提出了几点建议。更多还原

【Abstract】 Petroleum seismic data processing needs mass storage and computing, which has been an important application field of high performance computing. Linux-based cluster system has obvious advantages at the cost performance, reliability and scalability and has become the mainstream platform for seismic data processing. It can make full use of existing hardware and software resources to research the parallel efficiency of PC cluster for seismic data processing. It can not only improve the overall efficiency of seismic data processing cluster, but also improve the geological effects and economic benefits. Therefore, the issue has important practical significance.This paper analyzes the characteristics of seismic data processing system to identify the key factors that affect the parallel efficiency of PC cluster for seismic data processing,which are I/O bottleneck and serial programs’low operating efficiency in parallel environment. In order to solve the above problems, this paper conducts research in two areas: parallel file system and parallel programming.Firstly, a PC cluster is built using ordinary PC and MPI. We analyze the key factors that affect cluster performance through LINPACK benchmark and provide relevant suggestions.In order to solve the increasingly serious I/O bottleneck problem of seismic data processing cluster, we install Lustre parallel file system into the test cluster and make a comparison test between NFS and Lustre using iozone. The results show that Lustre can better meet the concurrent I/O requirements and effectively alleviate the I/O bottleneck. In order to improve the security of Lustre, this paper designs a Lustre security model based on PKI.The core algorithms of seismic data processing are FFT and matrix multiplication. We parallelize them using MPI, OpenMP and CUDA, and make a comparison in execute time between the parallel programs and related serial programs. Test results show that it can significantly reduce the run cycle by parallelizing the computing-intensive algorithms.We apply Lustre parallel file system and parallel programming techniques to real seismic data processing system. The real seismic data processing tests show that Lustre and parallel programming techniques can significantly reduce the seismic data processing cycle and improve the efficiency of procedures. In addition, this paper also investigates the effects of the compilers, runtime environment, math libraries and other factors on program efficiency and obtains some meaningful conclusions. Finally, several suggestions are given on further improve the parallel efficiency.更多还原