并行I/O中一种基于服务时间最小变化的文件分配策略

论文中对于文件访问的服务时间进行了较深入的研究,提出一种并行I/O文件分配算法——启发式文件分类分配策略,它在负载基本均衡前提下,按照相似的访问服务时间对每个待分配的数据文件进行磁盘分配。通过对启发式文件分类分配策略与已有的贪婪文件分配法进行实验比较,结果表明:系统处理重负载时,访问响应时间提高了30%左右,而且数据访问速率越高,由启发式文件分类分配策略所提高的性能就越明显。     

集群计算并行I/O中动态文件分配策略

针对集群计算系统中并行I／O文件分配问题进行了研究,提出一种新的动态文件分配算法一启发式负载与服务时间变化综合平衡策略。该策略将所需要的访问服务时间相似的文件分配到集群系统的同一结点磁盘上,并保证每个磁盘上的负载值不超过负载平衡的极限值,从而在所有结点磁盘间既基本实现负载均衡,又使每个磁盘上文件间的服务时间变化最小化。实验结果表明了该策略在性能提高方面的有效性。     

一种改进的基于缓存池机制的小文件I/O策略

Lustre文件系统对大文件的I/O性能较好,但对小文件不佳。针对这个问题,提出建立一个基于MDS节点的小文件缓存池机制,在缓存池里缓存经常被访问的小文件。在该机制中,小文件缓存池与OST使用全相联映射方式对应,并且使用贯穿读出式和直写式策略保持文件的一致性;缓存池更新策略综合考虑了文件的访问时间和次数等因素,使用改进的近期最少使用算法（LRU）更新替换。实验结果表明,改进后的Lustre文件系统减少了小文件的网络传输开销和访问时间,对小文件的I/O性能有较明显的提高。虽然它对大文件的I/O性能有所降低,但在可接受范围之内,仍具有一定的实用价值。     

基于RAM/Disk混合设备模型的FC-SAN存储系统

磁盘存取是基于光纤通道网络的SAN存储系统的目前性能瓶径，在综合和分析目前各种文件系统I／O操作工作负载的研究结果的基础上，提出了一个新的改进FC-SAN存储系统性能的方法：将各种文件系统I／O操作分为大数据量的文件读写操作、小数据量的文件读写操作和文件属性操作，大数据量的文件读写操作还是按照原来的I／O路径进行，存取物理磁盘；但其他各种文件操作包括小数据量的文件读写操作对基于内存的RAMDisk设备进行操作，实验结果显示，基于混合I／O子系统的FC-SAN存储系统的存取速率可以接近线速。     

并行文件系统自适应的文件条带化技术

研究并行文件系统自适应的文件条带(Striping)策略对改进文件访问性能的影响,并开发动态的文件条带分析模型,利用自动访问模式分类和实时文件系统性能数据为文件条带策略选择模糊逻辑规则库,来优化文件访问性能。研究结果表明：当文件系统负载低时,可以尽量将文件分布到所有磁盘上来最小化I/O的反馈时间;反之,在系统负载高时,使文件分布的范围小一些以便最大化文件系统整体的吞吐量。并通过实验给出了请求大小、请求宽度、请求到达率与系统性能的相互关系,实证了自适应规则库的正确性。     

基于内存映射文件的进化算法数据存储引擎

为了观察和分析进化算法的执行情况,往往需要将算法执行过程中产生的大量数据存储在磁盘文件中。用于进化算法的嵌入式数据存储引擎EADB（Evolutionary Algorithm Database）提供了简便灵活的数据存储接口,通过使用内存映射文件技术来实现数据的快速和大量存储。相较于传统文件I/O存储方式和一般的通用数据存储引擎,EADB大大加快了存储速度。     

高性能集群文件系统的研究

集群系统提供了强大的批处理和并行计算的能力,具有高性能、高可扩展性、高吞吐量和易用性等特点,但是I／O性能和处理器性能的不匹配使得I／O成为许多应用的瓶颈,特别是处理大量数据的应用就更是如此。针对集群系统当前的现状,克服该瓶颈的常用方法就是采用一种并行虚拟文件系统（PVFS）技术。随着Linux群集系统性能的持续提高,高速并行文件已成为并行计算的一个必备部分。并行虚拟文件系统（PVFS）为高性能计算（HPC）群集和大型I／O密集并行应用提供了这样一个文件系统。首先介绍了PVFS的结构;然后研究了PVFS的存取和管理机制;最后分析,PVFS的工作原理。     

Reference implementation of scalable I/O low-level API on Intel Paragon

The Scalable I/O(SIO)Initiative‘s Low-Level Application Programming Interface(SIO LLAP)provides file system implementers with a simple low-Level interface to support high-level parallel /O interfaces efficiently and effectively.This paper describes a reference implementation and the evaluation of the SIO LLAPI on the Intel Paragon multicomputer.The implementation provides the file system structure and striping algorithm compatible with the Parallel File System(PFS)of Intel Paragon ,and runs either inside the kernel or as a user level library.The scatter-gather addressing read/write,asynchronous I/O,client caching and prefetching mechanism,file access hint mechanism,collective I/O and highly efficient file copy have been implemented.The preliminary experience shows that the SIO LLAPI provides opportunities of significant performance improvement and is easy to implement.Some high level file system interfaces and applications such as PFS,ADIO and Hartree-Fock application,are also implemented on top of SIO.The performance of PFS is at least the same as that of Intel‘s native pfs,and in many cases,such as small sequential file access,huge I/O requests and collective I/O,it is stable and much better,The SIO features help to support high level interfaces easily,quickly and more efficiently,and the cache,prefetching,hints are useful to get better performance based on different access models.The scalability and performance of SIO are limited by the network latency,network scalable bandwidth,memory copy bandwidth,memory size and pattern of I/O requests.The tadeoff between generality and efficienc should be considered in implementation.     

IOMan:一种支持多操作系统远程启动和运行的I/O管理方法

为了降低用户使用和维护计算机系统的成本,基于透明计算模式提出了一种工作在局域网环境下的I/O管理方法:IOMan. IOMan只是用软件方法在客户端设置磁盘I/O重定向机制,按需动态下载数据,而不需要修改当前常用的操作系统如Windows的启动机制,也不影响其他I/O操作,能够支持多种操作系统的远程启动和应用程序的运行 . IOMan基于客户机/服务器模型,包括I/O Client和I/O Server两个部分,其中I/O Client工作在客户端,I/O Server工作在服务器端 . I/O Client通过重新定义访问磁盘的BIOS中断处理程序以及创建虚拟本地磁盘,将I/O请求发送给服务器;I/O Server响应客户端请求,读写服务器上存储的虚拟硬盘文件,然后以扇区形式将数据发送给I/O Client.     

I/O performance of an RAID-10 style parallel file system

Without any additional cost, all the disks on the nodes of a cluster can be connected together through CEFT-PVFS, an RAID-10 style parallel file system, to provide a multi-GB/s parallel I/O performance.I/O response time is one of the most important measures of quality of service for a client. When multiple clients submit data-intensive jobs at the same time, the response time experienced by the user is an indicator of the power of the cluster. In this paper, a queuing model is used to analyze in detail the average response time when multiple clients access CEFT-PVFS. The results reveal that response time is with a function of several operational parameters. The results show that I/O response time decreases with the increases in I/O buffer hit rate for read requests, write buffer size for write requests and the number of server nodes in the parallel file system, while the higher the I/O requests arrival rate, the longer the I/O response time. On the other hand, the collective power of a large cluster supported by CEFT-PVFS is shown to be able to sustain a steady and stable I/O response time for a relatively large range of the request arrival rate.     

一种高性能I／O方法

并存文伴系统是解决I／O瓶颈问题的重要途径。研究表明，科学应用中跨越式的文件访问模式与现存并行文件系统访问这些数据的方法的结合，对于大型数据集的访问其I／O性能是难以接受的。为了提高并行文件系统中对不连续数据的I／O性能，创建了一种新型高性能I／O方法：用户自定义文件视图结合合并I／O请求。并且在WPFS并行文件系统中实现了该方法。研究和实验结果表明，该方法具有增强科学应用性能的潜力。     

Fault tolerant file models for parallel file systems: introducing distribution patterns for every file

Parallelism in file systems is obtained by using several independent server nodes supporting one or more secondary storage devices. This approach increases the performance and scalability of the system, but a fault in one single node can stop the whole system. To avoid this problem, data must be stored using some kind of redundant technique, so any data stored in a faulty element can be recovered. Fault tolerance can be provided in I/O systems by using replication or RAID based schemes. However, most of the current systems apply the same technique for all files in the system. This paper describes the fault tolerance support provided by Expand, a parallel file system based on standard servers. This support can be applied to other parallel file systems with many benefices: fault tolerance at file level, flexible definition of fault tolerance scheme to be used, possibility to change the fault tolerant support used for a file, etc.

Filter Cache:一种提高Lustre I/O性能的方法

高性能计算系统需要一个可靠高效的并行文件系统.Lustre集群文件系统是典型的基于对象存储的集群文件系统,它适合大数据量聚合I/O操作.大文件I/O操作能够达到很高的带宽,但是小文件I/O性能低下.针对导致Lustre的设计中不利于小文件I/O操作的两个方面,提出了Filter Cache方法.在Lustre的OST组件中设计一个存放小文件I/O数据的Cache,让OST端的小文件I/O操作异步进行,以此来减少用户感知的小文件I/O操作完成的时间,提高小文件I/O操作的性能.     

基于集群的MPI主从式并行文件传输系统的研究与实现

研究并实现了一种基于PC集群系统的MPI主从式并行文件传输系统。通过引入一个监控节点实时监控当前各真实节点上的连接数、请求任务量以及各节点的实际处理能力,并衡量不同内容节点的负载,以实现集群内各节点负载均衡,从而更合理地实现并行文件I/O的任务分配。结果显示,该系统具有近似线性加速比,即文件I/O传输速度随着并行节点数量的增多而提高。     

SDAFT: A novel scalable data access framework for parallel BLAST

In order to run tasks in a parallel and load-balanced fashion, existing scientific parallel applications such as mpiBLAST introduce a data-initializing stage to move database fragments from shared storage to local cluster nodes. Unfortunately, with the exponentially increasing size of sequence databases in today’s big data era, such an approach is inefficient.In this paper, we develop a scalable data access framework to solve the data movement problem for scientific applications that are dominated by “read” operation for data analysis. SDAFT employs a distributed file system (DFS) to provide scalable data access for parallel sequence searches. SDAFT consists of two interlocked components: (1) a data centric load-balanced scheduler (DC-scheduler) to enforce data-process locality and (2) a translation layer to translate conventional parallel I/O operations into HDFS I/O. By experimenting our SDAFT prototype system with real-world database and queries at a wide variety of computing platforms, we found that SDAFT can reduce I/O cost by a factor of 4–10 and double the overall execution performance as compared with existing schemes.     

Exploring optimal combination of a file system and an I/O scheduler for underlying solid state disks

Performance and energy consumption of a solid state disk （SSD） highly depend on file systems and I/O schedulers in operating systems. To find an optimal combination of a file system and an I/O scheduler for SSDs, we use a metric called the aggregative indicator （AI）, which is the ratio of SSD performance value （e.g., data transfer rate in MB/s or throughput in IOPS） to that of energy consumption for an SSD. This metric aims to evaluate SSD performance per energy consumption and to study the SSD which delivers high performance at low energy consumption in a combination of a file system and an I/O scheduler. We also propose a metric called Cemp to study the changes of energy consumption and mean performance for an Intel SSD （SSD-I） when it provides the largest AI, lowest power, and highest performance, respectively. Using Cemp, we attempt to find the combination of a file system and an I/O scheduler to make SSD-I deliver a smooth change in energy consumption. We employ Filebench as a workload generator to simulate a wide range of workloads （i.e., varmail, fileserver, and webserver）, and explore optimM combinations of file systems and I/O schedulers （i.e., optimal values of AI） for tested SSDs under different workloads. Experimental results reveal that the proposed aggregative indicator is comprehensive for exploring the optimal combination of a file system and an I/O scheduler for SSDs, compared with an individual metric.     

并行文件系统PFS的设计与分析

并行计算机高速处理能力与低速Ｉ／Ｏ设备之间的矛盾目前已成为并行计算机系统中的主要问题之一，因此必须研制高性能的并行文件系统．。本文介绍的ＰＦＳ是为“八六三计划”中“曙光二号”并行计算机设计的并行文件系统，该ＰＦＳ分散Ｉ／Ｏ设备的管理到多个处理结点，使文件能交叉地分布在不同Ｉ／Ｏ结点所控制的物理设备上，以实现最大程度的并行访问。本文阐述了ＰＦＳ的基本设计、实现方法及其性能的粗略分析。     

基于I/O空闲率的硬盘功耗建模与评估方法研究

存储设备的功耗在整个计算机系统尤其是数据中心所占的比例已经越来越大。要进行硬盘功耗优化,在缺少硬件直接测量硬盘功耗的情况下就需要对硬盘功耗进行建模。现代操作系统通过文件系统层进行硬盘I/O操作管理,并提供实时监控数据。通过对EXT2、EXT4和NILFS2等常用文件系统的硬盘I/O过程进行实验分析,发现不同的文件系统对硬盘功耗具有不同的影响,为了刻画这种差异性,提出基于I/O空闲率的硬盘功耗建模与评估方法。同时使用I/O空闲率来指导硬盘进行功耗优化,将视频播放器的I/O空闲率由4.79%提高到96.55%,硬盘的功耗降低45.28%。     

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。     

存储设备块重组机制仿真研究

为了提高存储设备的I/O性能,设计了一种新的基于语义的块重组机制.该机制作为语义智能磁盘技术的一种应用,可以利用文件系统的语义信息推断磁盘块的相关性,并将语义相关的块移动到临近区域.块重组机制减少了访问文件时所需的寻道次数,提高了I/O性能.与其他块重组方法相比,该机制不依赖于历史访问信息,并且不受负载变化影响.通过仿真实验对该机制进行评测,实验结果表明,块重组机制能够有效减少I/O次数.