HPF高性能语言在地震资料并行处理中的应用

HPF（High Performance Fortran)是HPF论坛1993年推出的一种高性能数据并行语言。文章利用合作单位开发的p-HPF并行编译系统,在地震资料处理中得到了大规模的工业应用,基准测试程序和实际资料处理结果表明,基于HPF的地震资料并行处理具有可编程性强,可移植性好和并行效率高等特点,具有很好的应用前景。     

基于HPF的地震资料并行处理系统研究与实现

文中首先分析了地震资料并行处理的必要性，在介绍HPF高性能并行语言的特点后，着重讨论了p-HPF编译系统的体系结构与关键技术，然后，在分析地震资料自身特征和处理过程模块化程序设计的特点后，给出了地震资料处理的并行策略和一般SPMD程序的实现框图，最后，用一个简单的例子展示了HPF程序对于不同数据规模的并行效率，并用实际地震资料实现了大规模并行处理。     

基于规范划分集的并行循环编译框架

1 引言并行循环描述大多数先进科学应用的核心部分,是颇有价值的并行性来源。高级并行语言往往提供专门指导语句表达并行循环,以便并行编译器利用并行循环的非数据相关特性。在数据并行程序设计语言HPF中规定,可以将关键词INDEPENDENT加在Do循环前面,指出其后的Do循环是一个并行循环。与之相关的编译实现也成为HPF编译器的一个重点。并行循环L可以严格定义如下:假设R(i)表示迭代i所     

Cluster环境下p—HPF编译器支持的并行计算范式

p-HPF是研制的一个符合HPF（high performance Fortran)规范的并行编译系统,以HPF为核心实现多范式并行计算是开发大型并行应用系统的基础。首先论述了Cluster环境下的并行运行范式,包括farm parallel范式、流水线并行、流循环并行、基于数据并行和组合数据并行等,抽象分析了它们的性能,接着给出了利用p-HPF的外部过程机制、任务并行机制以以FORALL,INDEPENDENT DO等典型并行语句实现几种典型并行范式的方法,给出了实例程序,对实例进行了实际运行并对运行结果进行了分析。     

p—HPF支持多范例并行计算的并行编译技术

多范例并行是大规模并行应用系统的本质特征,实现p－HPF对多范例并行计算的编译支持不仅可以弥补数据并行示例本身的一些缺点,而且可以提高并行应用系统的效率,文中在论述cluster环境下Global,Local,Serial三种典型并行计算模型的基础上,给出了实现p－HPF对三种模型的典型代表F77＋MPI,ScaLAPACK调用的并行编译技术,包括参数重分布技术、存储转换技术、全局与局部信息交换技术以及局部数组参数的上下界处理技术等,给出了调用实例并分析了实现技术的正确性和有效性。     

基于分级存储的石油勘探地震处理应用研究

石油勘探中“两宽一高”采集技术的深入应用，对地震资料并行处理能力提出了更高的要求，针对存储对地震资料处理应用的影响进行研究。为提高各类应用的运算效率，设计并实现了基于SSD、集群NAS多级分层存储地震资料处理方法，针对高IOPS应用、大数据块并行应用进行算法流程级设计。通过DD与IOZONE基准测试、两种应用实际运行效果，验证了设计方案具备在地震资料处理中应用效率与性价比上的优势，适用于勘探数据中心地震资料处理，具有一定的普适性。     

一个基于NOW的跨平台并行文件系统的设计和实现

1.引言近年来,国内外对并行文件系统做了很多的研究,著名的有:一些商用的并行文件系统,如Intel为iPSC/2和iPSC/860而设计的CFS,以及IntelParagon的并行文件系统PPFS。还有HPF的运行支撑系统PASSION。研究性的则有PIOUS等。它们通常是针对并行机设计的,应用范围较为狭窄。随着对NOW(Network of Workstations,工作站网络)的研究深入,人们认识到NOW具有高速的交换     

一种HPF编译系统的研究与实现*

HPF(high performance Fortran)是一种典型的数据并行语言,HPF编译系统的实现是并行计算研究领域的一个难点.文章介绍了一个HPF编译系统的研究与实现情况,在对该系统的主要组成进行了简要介绍之后,着重讨论了系统实现中的若干关键技术,并列出了部分HPF源程序及其编译器生成的相应代码,最后给出了对该编译器的一些性能测试结果和有关问题的讨论.     

基于多层次并行算法的共成像点道集抽取

研究地表区域勘探和开发,应依靠地震偏移成像算法。在地震勘探中,利用叠前深度偏移抽取的共成像点道集为修正偏移速度提供了一种工具,然而庞大的计算量严重影响生产速度。为提高数据处理速度,提出了多层次并行共成点道集抽取算法,在集群节点间利用MPI并行,每个节点内部采用OpenMP并行,从而充分发挥每个节点的运算性能。实验结果表明,基于多层次并行的共成像点道集抽取具有良好的并行加速比和并行效率,有效提高了偏移速度分析的计算效率,为地震资料处理提供了更优的并行策略,并为油气勘探提供有效参考依据。     

基于SOPC的地震数据并行采集控制器设计

针对地震勘探仪器在多道数据并行采集控制技术上的瓶颈问题,提出基于嵌入式可编程片上系统的并行采集方案,开发了符合Avalon标准的"多道数据并行采集A/D组控制器"外设IP核,实现了多道数据严格并行采集控制,并成功应用在工程地震数据采集系统中。应用表明,该控制器能控制多道A/D转换器严格并行同步采样,具有同步精度高、非均匀误差小、通道扩展方便等优点,为地震勘探仪器高性能、低功耗、微型化设计提供了参考。     

基于MPI＋OpenMP混合模型的并行地震数据处理支撑库的研究

计算机集群技术已经引起了石油地球物理界的广泛关注，如何将现有地震数据处理模块快速、高效地移植到集群上已成为地震数据处理需要解决的重大课题。本文将现有的基于消息传递（MPI）的并行地震处理模型与共享存储（OpenMP）模型相结合，实现了一个适合于SMP集群的并行地震数据支撑库，将涉及到消息传递的并行地震数据操作以直观的API的形式提供给开发人员。本文利用支撑库提供的API开发了一些测试模块。实验证明，支撑库可支持现有地震数据处理和显示模块的多种并行计算模型，并且能够获得较高的并行加速比和计算效率。     

基于重叠变换的地震数据压缩去噪

近来有研究表明重叠正交变换(LOT)对压缩地震信号非常有效。与LOT相比,多分辨重叠双正交变换(HLBT)对信号频谱的非均匀划分,可以更加有效地将能量集中在有限的变换域子带(TransformBins)上。论文利用HLBT,针对地震数据中信号和噪声的特点,融合信号去噪和数据压缩,实现地震信号的高保真压缩。试验结果表明,对于高倍率的压缩,其效果要优于目前的小波压缩算法。     

Scalable multi-variate analytics of seismic and satellite-based observational data

Over the past few years, large human populations around the world have been affected by an increase in significant seismic activities. For both conducting basic scientific research and for setting critical government policies, it is crucial to be able to explore and understand seismic and geographical information obtained through all scientific instruments. In this work, we present a visual analytics system that enables explorative visualization of seismic data together with satellite-based observational data, and introduce a suite of visual analytical tools. Seismic and satellite data are integrated temporally and spatially. Users can select temporal ;and spatial ranges to zoom in on specific seismic events, as well as to inspect changes both during and after the events. Tools for designing high dimensional transfer functions have been developed to enable efficient and intuitive comprehension of the multi-modal data. Spread-sheet style comparisons are used for data drill-down as well as presentation. Comparisons between distinct seismic events are also provided for characterizing event-wise differences. Our system has been designed for scalability in terms of data size, complexity (i.e. number of modalities), and varying form factors of display environments.     

基于百度地图API的地震处置应用研究

针对传统地震处置应用存在的基础地理信息数据难获取、高涉密、难维护问题,设计一款基于百度地图API的地震处置应用,解决了基础地理信息数据使用问题。应用实践表明:地图API可以为地震处置应用提供数据支持,其数据分析功能能够直接用于地震处置数据分析。     

基于CUDA的地震数据层位面自动追踪算法

层位面追踪是三维地震数据解释的一项关键操作,对于地质勘探和油藏工程有重要的指导意义。传统的层位面自动追踪算法采用的是种子点蔓延法,该方法是一个不断进行迭代计算的过程。由于三维地震数据的数据量很大,传统的基于CPU的层位面自动追踪算法的计算效率不高。文中提出了一种基于CUDA的三维层位面自动追踪算法。该算法对种子点蔓延法进行了改进,实现了层位面自动追踪的GPU并行解决方案。实验表明,与传统的基于CPU的层位面自动追踪算法相比,本算法的计算效率有明显的提升。     

Artificial intelligence-enhanced seismic response prediction of reinforced concrete frames

Existing physics-based modeling approaches do not have a good compromise between performance and computational efficiency in predicting the seismic response of reinforced concrete (RC) frames, where high-fidelity models (e.g., fiber-based modeling method) have reasonable predictive performance but are computationally demanding, while more simplified models (e.g., shear building model) are the opposite. This paper proposes a novel artificial intelligence (AI)-enhanced computational method for seismic response prediction of RC frames which can remedy these problems. The proposed AI-enhanced method incorporates an AI technique with a shear building model, where the AI technique can directly utilize the real-world experimental data of RC columns to determine the lateral stiffness of each column in the target RC frame while the structural stiffness matrix is efficiently formulated via the shear building model. Therefore, this scheme can enhance prediction accuracy due to the use of real-world data while maintaining high computational efficiency due to the incorporation of the shear building model. Two data-driven seismic response solvers are developed to implement the proposed approach based on a database including 272 RC column specimens. Numerical results demonstrate that compared to the experimental data, the proposed method outperforms the fiber-based modeling approach in both prediction capability and computational efficiency and is a promising tool for accurate and efficient seismic response prediction of structural systems.     

Use of raster-based data layers to model spatial variation of seismotectonic data in probabilistic seismic hazard assessment

Recent achievements in computer and information technology have provided the necessary tools to extend the application of probabilistic seismic hazard mapping from its traditional engineering use to many other applications. Examples for such applications are risk mitigation, disaster management, post disaster recovery planning and catastrophe loss estimation and risk management. Due to the lack of proper knowledge with regard to factors controlling seismic hazards, there are always uncertainties associated with all steps involved in developing and using seismic hazard models. While some of these uncertainties can be controlled by more accurate and reliable input data, the majority of the data and assumptions used in seismic hazard studies remain with high uncertainties that contribute to the uncertainty of the final results. In this paper a new methodology for the assessment of seismic hazard is described. The proposed approach provides practical facility for better capture of spatial variations of seismological and tectonic characteristics, which allows better treatment of their uncertainties. In the proposed approach, GIS raster-based data models are used in order to model geographical features in a cell-based system. The cell-based source model proposed in this paper provides a framework for implementing many geographically referenced seismotectonic factors into seismic hazard modelling. Examples for such components are seismic source boundaries, rupture geometry, seismic activity rate, focal depth and the choice of attenuation functions. The proposed methodology provides improvements in several aspects of the standard analytical tools currently being used for assessment and mapping of regional seismic hazard. The proposed methodology makes the best use of the recent advancements in computer technology in both software and hardware. The proposed approach is well structured to be implemented using conventional GIS tools.     

Seismic noise attenuation by means of an anisotropic non-linear diffusion filter

Noise attenuation is a major seismic data processing concern. In seismic data, noise can appear as random, coherent and/or impulsive. Recently, many different techniques, ranging from relatively simple processes to extremely complex ones, have been used for noise attenuation. Image filtering techniques are relatively new methods in seismic exploration. We introduced the anisotropic non-linear diffusion filter which is an effective way to de-noise images. Since a seismic section can be considered as an image of a two-variable function, we implemented the anisotropic non-linear diffusion filter to reduce both random and Gaussian noises. This filter is shown to be effective in removing noise while preserving edges and hence reducing resolution loss in seismic data. The anisotropic non-linear diffusion filter, with Tukey's function to guide the diffusivity, was applied to synthetic and real seismic data. The results show a signal-to-noise ratio increase with reflector continuity in addition to better recovery of reflector amplitudes even when dealing with complex subsurface geological structures.     

存储虚拟化在石油物探的应用

随着石油物探向高密度单点、高精度、高分辨率地震技术方向发展,地震资料处理和解释领域正面临着数据存储挑战。要满足存储资源的统一集中管理、异构平台的地震数据共享、提升存储系统的利用率、I/O动态负载均衡等需求,提出了存储设备级与存储网络级结合的存储虚拟化思想,设计了一种实现方案,对地震资料处理与解释中的存储系统进行了逻辑卷级和文件系统级虚拟化,并对其优越性进行了分析与验证。     

循环载荷作用下两类楼板抗震性能的非线性有限元分析

为比较组合楼板和普通混凝土楼板的抗震性能,采用非线性有限元分析方法研究它们在循环载荷作用下的受力行为,并由此得到两类楼板的滞回曲线、骨架曲线及应力应变分布规律．计算结果表明,采用可靠构造措施的压型钢板与混凝土组合作用明显,在不失较高承载力的同时,组合楼板仍具有良好的抗震性能．将计算结果与试验数据相比较,验证该数值分析方法的有效性。