并行文件系统I/O特征

并行文件系统是并行计算系统的存储子系统,I/O性能是并行计算系统研究的重要方面.本文分析了并行文件系统I/O研究的难点,研究了并行文件系统的I/O特征和关键技术,指出了并行文件系统I/O性能研究未来的研究方向,为并行计算系统的设计和优化提供重要参考.     

一种动态并行I/O调度新策略的研究

并行I/O已经成为提高分布式计算系统性能的一种重要方式,论文在研究集群计算系统并行I/O数据调度策略的基础上,提出了一种应用于分布式计算系统中的二次调度自主维护负载平衡的动态I/O调度算法(DIO_TSMB),实验结果表明了算法的有效性,最后分析了并行I/O数据调度的发展趋势。     

集群环境下I/O文件传输调度器的设计与实现

近年来研究人员对高性能计算中的并行I/O问题进行了深入研究,然而这些研究主要针对MPP问题,而对集群计算机系统中并行I/O问题的研究不多。因此,对于集群计算中的并行I/O系统进行研究是一个重要的研究课题。对集群计算中的并行I/O传输调度效率进行研究,设计了一个文件传输调度器,可以实现文件传输最快捷,节点资源最大利用,显著提高I/O节点吞吐率和反应时间。经过大量数据的测试和实验证明该调度器的有效性和适用性。     

一种共享对象存储的并行文件系统设计

高可用和动态可扩展特性是并行文件系统设计实现中的难点.利用对象存储在I/O性能、可用性和可扩展性方面的优势,提出一种共享对象存储的并行文件系统设计,在保证高性能I/O的基础上,侧重提高系统的可用性和动态可扩展性.     

磁盘阵列系统I/O调度优化研究

分析了RAID-10系统的并行I/O任务模型,应用模糊函数提出了衡量I/O服务的满意度指标,并应用此指标,提出了一种适用于RAID-10系统I/O任务调度算法,提高了RAID-10系统的实时性能,并改善了负载其平衡能力。     

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。     

集群计算系统中并行I/O访问的自适应调度策略

现代计算机系统的性能已经由受限于CPU转变为受限于I／O，因此，并行I／O是缓解这一难题的有效方法。文章通过对集群计算系统中I／O调度策略的研究，提出了一种新的自适应平等划分的I／O调度策略，并将它们与已经存在的调度策略进行比较。实验结果表明了所提出策略的优越性。     

并行文件系统Lustre细粒度I/O性能优化

并行文件系统Lustre粗粒度I/O性能良好,细粒度I/O性能相对粗粒度I/O比较低下,因此优化细粒度I/O性能成为提高系统整体I/O性能的关键问题。在研究和分析了Lustre的I/O访问模式、细粒度I/O服务流程和页面替换算法等方面后,提出了细粒度优先（Fine Grained First,FGF）LRU算法。在OST端及Client端的页高速缓存中最大程度地保留细粒度I/O的页面,降低细粒度I/O引起的页面下沉速度,延长细粒度I/O页面在主存中的时间,进而减少对磁盘的访问次数,降低磁盘访问开销。通过对实验数据的对比和分析,验证了FGF-LRU算法的有效性。在不影响粗粒度I/O性能的情况下,提高了细粒度I/O性能,最终实现提高系统整体I/O性能。     

I/O系统性能测评与分析

输入输出系统(I/O系统)作为计算机系统中的一个重要组成部分,其性能的好坏对CPU的性能有很大的影响,因此本文从I/O系统基本概述开始介绍,并采用了模型模拟和实际测量的方法来衡量I/O系统性能,并做了相关的评价分析.     

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。     

可伸缩分布共享大规模并行I／O系统设计

如何有效地解决I／O瓶颈问题，一直是高性能并行计算机有待研究解决的关键技术。我们提出了一种可伸缩分布共享并行I／O系统方案，并自行研制了结点控制器芯片和路由器芯片，研制了原型系统SDSP604。为实现系统的计算、通讯和I／O性能随着系统规模均衡扩展的目标，该系统基于CC-NUMA系统结构，采用了合理的分布共享并行I／O系统结构。     

Quantitative characterization and analysis of the I/O behavior of acommercial distributed-shared-memory machine

This paper presents a unified evaluation of the I/O behavior of a commercial clustered DSM machine, the HP Exemplar. Our study has the following objectives: 1) To evaluate the impact of different interacting system components, namely, architecture, operating system, and programming model, on the overall I/O behavior and identify possible performance bottlenecks, and 2) To provide hints to the users for achieving high out-of-box I/O throughput. We find that for the DSM machines that are built as a cluster of SMP nodes, integrated clustering of computing and I/O resources, both hardware and software, is not advantageous for two reasons. First, within an SMP node, the I/O bandwidth is often restricted by the performance of the peripheral components and cannot match the memory bandwidth. Second, since the I/O resources are shared as a global resource, the file-access costs become nonuniform and the I/O behavior of the entire system, in terms of both scalability and balance, degrades. We observe that the buffered I/O performance is determined not only by the I/O subsystem, but also by the programming model, global-shared memory subsystem, and data-communication mechanism. Moreover, programming-model support can be used effectively to overcome the performance constraints created by the architecture and operating system. For example, on the HP Exemplar, users can achieve high I/O throughput by using features of the programming model that balance the sharing and locality of the user buffers and file systems. Finally, we believe that at present, the I/O subsystems are being designed in isolation, and there is a need for mending the traditional memory-oriented design approach to address this problem     

一种新型高效共享的并行I/O系统

如何有效地解决I／O瓶颈问题，一直是高性能并行计算机有待解决的关键技术。该文提出了一种高效共享的并行I／O系统——HPPIO，该系统基于CC-NUMA并行系统结构，采用了一系列高效共享、并行I／O技术。该文对其分布与集中相结合的高效共享并行I／O系统结构、基于PCI Express的高性能I／O控制器设计等进行了介绍。     

SPP外围子系统的设计与实现

并行处理机外围子系统的设计和实现技术直接影响整个系统的性能价格比，本文根据ＳＰＰ体系结构的特点和实际应用需要，在前端服务器与ＳＭ／ＳＳＭ之间设计了专用的Ｉ／Ｏ处理机，使得系统Ｉ／Ｏ设备与ＳＭ／ＳＳＭ之间直接进行高速数据传送，从而大大提高系统的Ｉ／Ｏ性能。在Ｉ／Ｏ处理机的设计中，采用了ｉ８６０＋８２３８０＋ＳＲＡＭ的总体结构，从而实现了处理机访问主存和ＤＭＡ控制器访问ＳＲＡＭ之间的并行。     

Heuristics for scheduling I/O operations

The I/O bottleneck in parallel computer systems has recently begun receiving increasing interest. Most attention has focused on improving the performance of I/O devices using fairly low level parallelism in techniques such as disk striping and interleaving. Widely applicable solutions, however, will require an integrated approach which addresses the problem at multiple system levels, including applications, systems software, and architecture. We propose that within the context of such an integrated approach, scheduling parallel I/O operations will become increasingly attractive and can potentially provide substantial performance benefits. We describe a simple I/O scheduling problem and present approximate algorithms for its solution. The costs of using these algorithms in terms of execution time, and the benefits in terms of reduced time to complete a batch of I/O operations, are compared with the situations in which no scheduling is used, and in which an optimal scheduling algorithm is used. The comparison is performed both theoretically and experimentally. We have found that, in exchange for a small execution time overhead, the approximate scheduling algorithms can provide substantial improvements in I/O completion times     

Client-side straggler-aware I/O scheduler for object-based parallel file systems

Object-based parallel file systems have emerged as promising storage solutions for high-performance computing (HPC) systems. Despite the fact that object storage provides a flexible interface, scheduling highly concurrent I/O requests that access a large number of objects still remains as a challenging problem, especially in the case when stragglers (storage servers that are significantly slower than others) exist in the system. An efficient I/O scheduler needs to avoid possible stragglers to achieve low latency and high throughput. In this paper, we introduce a log-assisted straggler-aware I/O scheduling to mitigate the impact of storage server stragglers. The contribution of this study is threefold. First, we introduce a client-side, log-assisted, straggler-aware I/O scheduler architecture to tackle the storage straggler issue in HPC systems. Second, we present three scheduling algorithms that can make efficient decision for scheduling I/Os while avoiding stragglers based on such an architecture. Third, we evaluate the proposed I/O scheduler using simulations, and the simulation results have confirmed the promise of the newly introduced straggler-aware I/O scheduler.     

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。     

并行网络文件系统PNFS性能评测与分析

传统的网络文件系统难以满足高性能计算系统的I/O 需求,并行网络文件系统——PNFS可以有效地解决传统网络文件系统在可扩展性、可用性和性能上存在的问题。首先对PNFS的体系结构进行了设计,实现了元数据服务器与存储服务器的分离,消除了由于集中服务器结构引发的I/O瓶颈问题。然后,对PNFS的原型系统进行了性能测试,并与相同环境下NFS的测试结果进行比较与分析,结果表明PNFS能够为客户端提供并行访问文件数据的能力,有着较高的I/O读写带宽和较低的访问延迟,同时实现了客户端I/O带宽与存储服务器规模之间的线性可扩展关系,能较好地满足高性能计算中的I/O需求。     

Current issues in high performance computing I/O architectures and systems

The abundance of parallel and distributed computing platforms, such as MPP, SMP, and the Beowulf clusters, to name just a few, has added many more possibilities and challenges to high performance computing (HPC), parallel I/O, mass data storage, scalable architectures, and large-scale simulations, which traditionally belong to the realm of custom-tailored parallel systems. The intent of this special issue is to discuss problems and solutions, to identify new issues, and to help shape future research directions in these areas. From these perspectives, this special issue addresses the problems encountered at the hardware, architectural, and application levels, while providing conceptual as well as empirical treatments to the current issues in high performance computing, and the I/O architectures and systems utilized therein.     

Analysis of I/O Performance on an Amazon EC2 Cluster Compute and High I/O Platform

Cloud computing is currently being explored by the scientific community to assess its suitability for High Performance Computing (HPC) environments. In this novel paradigm, compute and storage resources, as well as applications, can be dynamically provisioned on a pay-per-use basis. This paper presents a thorough evaluation of the I/O storage subsystem using the Amazon EC2 Cluster Compute platform and the recent High I/O instance type, to determine its suitability for I/O-intensive applications. The evaluation has been carried out at different layers using representative benchmarks in order to evaluate the low-level cloud storage devices available in Amazon EC2, ephemeral disks and Elastic Block Store (EBS) volumes, both on local and distributed file systems. In addition, several I/O interfaces (POSIX, MPI-IO and HDF5) commonly used by scientific workloads have also been assessed. Furthermore, the scalability of a representative parallel I/O code has also been analyzed at the application level, taking into account both performance and cost metrics. The analysis of the experimental results has shown that available cloud storage devices can have different performance characteristics and usage constraints. Our comprehensive evaluation can help scientists to increase significantly (up to several times) the performance of I/O-intensive applications in Amazon EC2 cloud. An example of optimal configuration that can maximize I/O performance in this cloud is the use of a RAID 0 of 2 ephemeral disks, TCP with 9,000 bytes MTU, NFS async and MPI-IO on the High I/O instance type, which provides ephemeral disks backed by Solid State Drive (SSD) technology.