地理栅格数据的并行访问方法研究

在海量地理栅格数据处理中,数据I/O性能是影响处理算法程序整体性能的关键。目前针对地理栅格数据 I/O优化问题的研究成果还很有限,通过对并行程序中的数据I/O模式进行深入分析,结合栅格数据逻辑模型和物理 模型的特点,提出了面向地理栅格数据的并行I/O框架;基于消息传递模型,实现了4种并行访问方法。实验证明,并 行访问方法优于传统的串行访问方法和分时多进程访问方法。该研究成果可以提高并行栅格处理程序的I/()访问效 率,进而提高其整体并行性能。     

基于MPI的并行I/O方法

基于MPI-2规范的并行I/O方法,以并行矩阵乘法问题为例,比较了并行I/O和串行I/O的性能,给出了并行I/O方法的应用实例。     

基干MPI的并行I/0方法

基于MPI-2规范的并行I/O方法,以并行矩阵乘法问题为例,比较了并行I/O和串行I/O的性能,给出了并行I/O方法的应用实例.     

新型非易失相变存储器PCM应用研究

并行I/O技术有效优化了I/O性能,但对访问延迟却难以控制.相变存储器(phase change memory,PCM)作为一种SCM(storage class memory),具有非易失性、随机可读写、低延迟、高吞吐率、体积小和低功耗的特点,为I/O性能优化提供了最直接有效的途径.研究了PCM的特性与存在的问题,总结了目前PCM的应用研究进展,针对高性能计算中的并行I/O问题,提出了一种基于相变存储器PCM的层次式并行混合存储模型,能够有效提高并行文件系统元数据服务效率和并行I/O吞吐率.     

使用MPI的并行I/O实现及性能分析

论文讨论了并行环境中I/O的基本方法——串行I/O方法和并行I/O方法,并使用MPI-1及MPI-2对这两种方法进行了实现。分析了不同的实现方法对I/O带宽产生的影响。通过理论分析和实验表明,基于MPI-2的并行I/O实现方法与其它I/O实现方法相比,可得到更高的I/O带宽,是解决I/O性能问题的有效途径。     

I/O受限的并行加速比模型与可扩展I/O体系结构

为了缓解I/O瓶颈问题,可以从应用程序、可扩展算法、编译器和语言、运行时库、操作系统和体系结构六方面展开研究。其中,I/O体系结构是所有技术途径的关键支撑。当前并行I/O性能分析缺乏科学的理论模型为I/O体系结构设计提供理论依据。本文针对并行计算机系统的可扩展性问题,研究了I/O负载对并行计算机系统可扩展性的影响,建立了I/O受限的并行加速比性能模型,对目前大规模并行计算机系统中三种常用I/O体系结构的可扩展性进行了分析;以此为理论依据,提出了一种面向高性能计算的可扩展并行I/O系统结构。同时,还提出了几种有效降低I/O操作服务时间的策略,从而达到增强系统可扩展性的目的,为后续研究奠定了基础。     

集群计算系统中并行I/O模拟器的研究与设计

论文对集群计算系统中的并行I／O技术作了分析，在理论研究基础上提出并行I／O模拟器的框架模型及研究、设计该模拟器的思路，并开发了一个并行I／O模拟器CLU—PIO—SIM的部分功能。     

基于HDF5的结构网格计算流体动力学程序并行I/O技术

大规模计算流体动力学(CFD)计算对数据I/O能力提出了很高需求。层次式文件格式(HDF5)可有效管理大规模科学数据,并对并行I/O具有良好的支持。针对结构网格CFD并行程序,设计了其数据文件的HDF5存储模式,并基于HDF5并行I/O编程接口实现了其数据文件的并行I/O,在并行计算机系统上进行了性能测试与分析。结果表明,在使用4~32个进程时,基于HDF5并行I/O方式的写文件性能比每进程独立写普通文件的方式高6.9~16.1倍;基于HDF5并行I/O方式的读文件性能不及后者,为后者的20%~70%,但是读文件的时间开销远小于写文件的时间开销,因此对总体性能的影响较小。     

基于HD F5实现多区结构网格CFD程序的并行I/O

计算流体动力学（computational fluid dynamics ,CFD）是高性能计算重要应用领域之一,其计算涉及大量数据访问．在大规模并行计算情况下,串行I/O的性能与计算能力不匹配,I/O成为性能瓶颈．并行I/O 是解决这一问题的主要途径之一．针对一个真实多区结构网格CFD 并行程序 HOSTA （high‐order simulator for aerodynamics）,基于HDF5（hierarchical data format v5）数据存储格式及其并行I/O编程接口,实现了其主要数据的并行I/O．在一套有6个I/O服务器结点的高性能计算机系统上,采用实际C FD算例进行了性能测试．对一个三角翼算例,并行I/O相对于串行I/O的性能加速比达到21．27,最高获得5．81 GBps的I/O吞吐率,并使程序整体性能提高10％以上;对一个网格规模更大的简单翼型算例,并行I/O最高获得了6．72 GBps的I/O吞吐率．     

并行科学计算应用中采样数据的聚集I/O

采样数据的并行I/O制约一些并行应用的运行效率。设计、实现了采样数据的聚集并行I/O方法。该方法在客户端部署采样数据缓存,然后合并数据到输出进程,再存储到文件。为了保障并行程序长时间运行过程中采样数据的存储一致性,该方法在JASMIN框架中监测应用程序的运行状态,当并行程序发生负载平衡或者重启动时刷新或者恢复数据。I/O过程中,进一步使用HDF5的分块I/O提高列存储数据的读写效率。测试表明,新方法不仅具有较好的可扩展性,还能在具有负载平衡与重启动等复杂功能的并行应用中提高采样数据的并行 I/O 效率7.5倍以上。     

VBMq: pursuit baremetal performance by embracing block I/O parallelism in virtualization

Barely acceptable block I/O performance prevents virtualization from being widely used in the High-Performance Computing field. Although the virtio paravirtual framework brings great I/O performance improvement, there is a sharp performance degradation when accessing high-performance NAND-flash-based devices in the virtual machine due to their data parallel design. The primary cause of this fact is the deficiency of block I/O parallelism in hypervisor, such as KVM and Xen. In this paper, we propose a novel design of block I/O layer for virtualization, named VBMq. VBMq is based on virtio paravirtual I/O model, aiming to solve the block I/O parallelism issue in virtualization. It uses multiple dedicated I/O threads to handle I/O requests in parallel. In the meanwhile, we use polling mechanism to alleviate overheads caused by the frequent context switches of the VM’s notification to and from its hypervisor. Each dedicated I/O thread is assigned to a non-overlapping core to improve performance by avoiding unnecessary scheduling. In addition, we configure CPU affinity to optimize I/O completion for each request. The CPU affinity setting is very helpful to reduce CPU cache miss rate and increase CPU efficiency. The prototype system is based on Linux 4.1 kernel and QEMU 2.3.1. Our measurements show that the proposed method scales graciously in the multi-core environment, and provides performance which is 39.6x better than the baseline at most, and approaches bare-metal performance.     

A model of checkpoint behavior for applications that have I/O

Due to the increase and complexity of computer systems, reducing the overhead of fault tolerance techniques has become important in recent years. One technique in fault tolerance is checkpointing, which saves a snapshot with the information that has been computed up to a specific moment, suspending the execution of the application, consuming I/O resources and network bandwidth. Characterizing the files that are generated when performing the checkpoint of a parallel application is useful to determine the resources consumed and their impact on the I/O system. It is also important to characterize the application that performs checkpoints, and one of these characteristics is whether the application does I/O. In this paper, we present a model of checkpoint behavior for parallel applications that performs I/O; this depends on the application and on other factors such as the number of processes, the mapping of processes and the type of I/O used. These characteristics will also influence scalability, the resources consumed and their impact on the IO system. Our model describes the behavior of the checkpoint size based on the characteristics of the system and the type (or model) of I/O used, such as the number I/O aggregator processes, the buffering size utilized by the two-phase I/O optimization technique and components of collective file I/O operations. The BT benchmark and FLASH I/O are analyzed under different configurations of aggregator processes and buffer size to explain our approach. The model can be useful when selecting what type of checkpoint configuration is more appropriate according to the applications’ characteristics and resources available. Thus, the user will be able to know how much storage space the checkpoint consumes and how much the application consumes, in order to establish policies that help improve the distribution of resources.

     

基于SANs模型的一种并行I/O系统的可用性评估

并行I/O系统是高性能计算机系统的一个重要组成部分,其可用性水平对整机系统性能的发挥具有重要作用。采用SANs(Stochastic Activity Networks,随机行为网)模型及其支持工具Mobius,对一种大规模并行I/O系统建立可用性评估模型,并采用模拟方法进行解析。模拟结果反映了全局文件系统数量、单一文件系统内最小可用OST(Object Storage Target,对象存储目标)数量和系统维修时间等参数的变化对全系统可用度的影响,对于大规模并行I/O系统的设计与维护具有积极的参考价值。     

并行数据库系统中并行I／O的研究与实现

并行Ｉ／Ｏ是基于无共享结构的并行数据库系统提高性能的有效途径之一。它通过并行磁盘服务和网络传输并行化提供了高带宽Ｉ／Ｏ。文章设计实现了基于无共享结构的并行数据库系统的并行Ｉ／Ｏ,探讨了设计并行Ｉ／Ｏ时的几个关键问题及实现技术。     

Performance Evaluation of a Parallel Pipeline Computational Model for Space-Time Adaptive Processing

This paper presents further results on the design and implementation of various optimizations based on our earlier work of developing a parallel pipelined model for the computational intensive applications that have multiple processing tasks. Performance evaluation of this model was done by using a real-time airborne radar application that employs a Space-Time Adaptive Processing (STAP) algorithm. This paper focuses on the following four issues: (1) The tradeoffs between increasing the throughput and reducing the latency are examined in more detail when allocating processors among different processing tasks. (2) A multi-threaded design is incorporated into the pipeline model and implemented on a massively parallel computer with symmetric multi-processor nodes, which shows enhanced performance. (3) The disk I/O is incorporated into the parallel pipeline to study its effect on performance in which two I/O task designs have been implemented: embedding I/O in the pipeline or having a separate I/O task. By using a double buffering approach together with the asynchronous I/O, the overall pipeline performance scales well as the number of processors increases. (4) From the comparison of the two I/O implementations, it is discovered that the latency may be improved when merging multiple tasks into a single task. The effect of reorganizing the task structure of the pipeline is discussed in detail. All the performance results shown in this work demonstrate the linear scalability the parallel pipeline model can achieve using a production radar application. Although this paper focuses on the implementation of the parallel pipeline model and uses the results from a STAP application to support the claims of the discovered properties for this pipeline, this model is also applicable to many other types of applications with similar computational characteristics.     

并行I/O技术在气候数值模式中的应用研究

在气候变化数值模拟工作中,气候数值模式运行效率主要受到计算效率和I/O效率的共同影响。目前,模式计算部分已经基本实现并行,计算效率显著提升。随着气候数值模式时空分辨率的提高,对I/O效率的需求也不断增加,数据并行I/O技术已经成为提高模式整体运行效率的有效方法之一。文中深入分析了BCC_AGCM模式串行I/O算法及NetCDF数据结构特点,采用基于MPI-IO的高层I/O库对模式I/O算法进行并行优化,优化后可支持多类气象要素并行输出,输出效率明显提升。为我国应对气候变化数值模式的运行效率优化工作,进行了有益的技术探索和积累。