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By Ali Alskaykha PARALLEL VIRTUAL FILE SYSTEM PVFS PVFS Distributed File System:

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Presentation on theme: "By Ali Alskaykha PARALLEL VIRTUAL FILE SYSTEM PVFS PVFS Distributed File System:"— Presentation transcript:

1 By Ali Alskaykha PARALLEL VIRTUAL FILE SYSTEM PVFS PVFS Distributed File System:

2 Outline  Before PVFS  PVFS Definition  Develop PVFS  Objectives and Goals  Architecture  PVFS  Cooperative Cache for PVFS (Coopc-PVFS)  Performance  PVFS2 and Improvements  Summary

3 Before PVFS If my business has exploded, my desktops are out of storage, and information is scattered everywhere! Each user keeps his files on his PC; when someone needs a file they grab it with a USB flash drive or via . When business grew the PCs are running out of storage. That's time to consolidate, centralize, and share file storage across the network. There are three basic ways: 1. Direct-Attached Storage (DAS) Direct attached storage refers to the storage attached directly to a PC or server

4 Before PVFS If my business has exploded, my desktops are out of storage, and information is scattered everywhere! 2. Storage Area Network (SAN) An alternative to using DAS is to separate storage from your servers and put it on its own specialized, high performance storage network called a storage area network (SAN)

5 Before PVFS If my business has exploded, my desktops are out of storage, and information is scattered everywhere! 3. Network File System (NFS) NFS is a client/server application developed by Sun Microsystems It lets a user view, store and update files on a remote computer as though the files were on the user's local machine. The basic function of the NFS server is to allow its file systems to be accessed by any computer on an IP network. NFS clients access the server files by mounting the servers exported file systems.

6 Before PVFS If my business has exploded, my desktops are out of storage, and information is scattered everywhere!  Having all your data stored in a central location presents a number of problems:  Scalability: arises when the number of computing nodes exceeds the performance capacity of the machine exporting the file system; could add more memory, processing power and network interfaces at the NFS server, but you will soon run out of CPU, memory and PCI slots; the higher the node count, the less bandwidth (file I/O) individual node processes end up with  Availability: if NFS server goes down all the processing nodes have to wait until the server comes back into life.  Solution: Parallel Virtual File System ( PVFS )

7 Parallel Virtual File System(PVFS) Parallel Virtual File System(PVFS)  Parallel Virtual File System (PVFS) is an open source implementation of a parallel file system developed specifically for Beowulf class parallel computers and Linux operating system  It is joint project between Clemson University and Argonne National Laboratory  PVFS has been released and supported under a GPL license since  File System – allows users to store and retrieve data using common file access methods (open, close, read, write)  Parallel – stores data on multiple independent machines with separate network connections  Virtual – exists as a set of user-space daemons storing data on local file systems

8 Develop PVFS 1993  First developed in 1993 as parallel file system  To study I/O patterns of parallel programs  1994  1994, PVFS version 1 for a cluster of DEC Alpha workstations   1994, PVFS version 1 ported to Linux, released 1997 as open source   1999, PVFS version 2 (PVFS2) developed, released 2003  2005  2005, PVFS version 1 retired

9 PVFS  Open source parallel file system for Linux clusters  Distributes file data across multiple nodes  Provides concurrent file access from multiple tasks (clients) node Client File concurrent file access File data distributed

10 Objectives  Objectives  Needed basic software platform to purpose further research in parallel I/O and parallel file systems for Linux clusters  Need of parallel file system for Linux clusters for high- performance I/O

11 Goals  Goals  Provide high-bandwidth access to file data for concurrent read/write operations from multiple tasks  Support multiple I/O APIs: Native PVFS API Native PVFS API UNIX/POSIX I/O API UNIX/POSIX I/O API MPI-IO MPI-IO  Robust and scalable  Easy for others to install and use


13 Design Overview  Client-server system with multiple nodes  User specifies which nodes serves as I/O nodes (servers)  Files are striped across I/O nodes; this provides multiple paths to data to achieve high-bandwidth access  I/O daemons run on I/O nodes to handle local file storage I/O node I/O daemon Client File

14 Design Overview (cont’d)  Single manger daemon to manage storage and access to all metadata of PVFS files  Read/write is handled by client library and I/O daemons  TCP for internal communication  User-level implementation; no kernel modifications needed  Linux kernel module is available

15 File Metadata Manager I/O node 0 I/O node 1 I/O node 2 I/O node 3 I/O node 4 I/O node 5 inode. base pcount ssize Metadata Stripe size: bytes /local/f12345  Manger daemon manages storage of and access to all metadata  Metadata describes characteristics of file: permissions, owner/group, and physical distribution of file data File: /pvfs/foo /pvfs/foo Manger Daemon

16 I/O File Access and Data Storage  I/O daemons handles I/O file access and the storage of its file portion on local file system on the I/O node  Clients establish connections with I/O daemons to perform read/write operations  Client library sends descriptor of file region a client wants to access to I/O daemons I/O node I/O daemon Client File Establish connection Client Library Sends descriptor

17 Cooperative Cache (Coopc-PVFS)  Created for PVFS because PVFS does not support file system caching facility (client side)  To reduce servers’ load and increase high performance  Client caches file blocks in client’s memory  Cached file blocks shared among clients  File block requests managed by a cache manager  Scalable as number of clients increases  More memory in cooperative cache than in single file system cache

18 Coopc-PVFS Design  Coopc-PVFS added to the PVFS kernel module  Cache manger manages cache blocks (I/O Node) (Manager Daemon)

19 Coopc-PVFS Info Management  Hint-based cooperative cache: method to maintain accurate information about cached blocks in clients  Manager Daemon keeps list of clients that opened file before  Client that opens file gets metadata of file and opened clients lists  Cache manager exchanges information about cached blocks with other clients’ cache manager when client reads a block that’s not in its cache

20 Coopc-PVFS Consistency  Cache manger invalidates blocks cached in other clients before writing block to I/O node (server) Application Cache Manager Manager Daemon I/O node Writes to block Block invalidation propagation request Invalidate Write block to I/O node

21 Coopc-PVFS Implementation  Cache manager does the memory management of cache blocks. Allocates cache blocks from kernel memory


23 Test Types  PVFS tested on two different high-speed networks:  Fast Ethernet vs Myrinet  Coopc-PVFS:  PVFS vs Coopc-PVFS  Cache vs No cache

24 PVFS Test Config  60 nodes:  some as I/O nodes  some as compute nodes  Disk transfer rate: 13.5 to 21.5 MB/sec  File-stripe size: 16 KB  Variants for testing on Fast Ethernet and Myrinet:  Number of I/O nodes accessed  Compute nodes  I/O file size

25 Fast Ethernet Results 46 MB/sec 90 MB/sec 177 MB/sec 42 MB/sec 83 MB/sec 166 MB/sec Reached limit of scalability with 24 compute nodes 222 MB/sec 226 MB/sec

26 Myrinet Results 138 MB/sec 255 MB/sec 450 MB/sec 93 MB/sec 180 MB/sec 325 MB/sec 650 MB/sec 687 MB/sec 460 MB/sec 670 MB/sec Largest number of compute nodes tested: 45

27 BTIO Benchmark Results  Matrix computation is done then writes solution data to a file at time intervals  Fix number of 16 I/O nodes was used MB/sec

28 Coopc-PVFS Test Config  6 nodes:  Disk transfer rate: 13.5 to 21.5 MB/sec  File-stripe size: 64 KB  Variants for testing:  I/O node (sever) cache and no cache  Coopc-PVFS cache and no cache Manager Daemon I/O nodeclient

29 Coopc-PVFS Matrix Multi Test Server No Cache Server Cache No one caches Server cache Coopc cache data PVFSCoopc-PVFS  Matrix Multiplication program is read-dominant program  Read time reduced to almost 0 in Coopc-PVFS because file is cached once it is read  When server doesn’t cache in PVFS, Waiting time is larger than other cases because read time is larger than other cases

30 Coopc-PVFS BTIO Benchmark  BTIO benchmark programs are write-dominant  Used 4 BTIO programs  Read time of Coopc-PVFS shorter than in PVFS because clients cache files  Write time of Coopc-PVFS is longer than in PVFS

31 PVFS2 and Improvements  Distributed metadata to avoid single point of failure and performance bottleneck  As systems continue to scale it becomes ever more likely that any such single point of contact might become a bottleneck for applications  Stateless servers and clients (no locking subsystems)  If server crashes another can be restarted  Added redundancy support

32 Summary  PVFS  High performance parallel I/O for Linux clusters  Scalable as number of I/O nodes increases  Supports multiple I/O APIs  Performance benefits from high-speed network  Cooperative Cache for PVFS  Allows client to request file to another client instead of server  Scalable as number of clients increases  Block invalidation for consistency (client-initiated validation)  Improves performance for reading, but not for writing

33 Works Cited  Philip H. Carns, Walter B. Ligon, III, Robert B. Ross and Rajeev Thakur, "PVFS: A Parallel File System for Linux Clusters," In Proc. of the 4th Annual Linux Showcase and Conference, October 2000, pages  In-Chul Hwang, Hojoong Kim, Hanjo Jung, Dong-Hwan Kim, Hojin Ghim, Seung-Ryoul Maeng, and Jung-Wan Cho, "Design and Implementation of the Cooperative Cache for PVFS", Lecture Notes in Computer Science, Volume 3036/2004, pages 43 – 50  PVFS website  (old)  (current)  Parallel Virtual File System Wiki 

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