Parallel and Grid I/O Infrastructure

1
Parallel and Grid I/O Infrastructure

• Rob Ross Argonne National Lab
• Parallel Disk Access and Grid I/O (P4)
• SDM All Hands Meeting
• March 26 2002

2
Participants

• Argonne National Laboratory
• Bill Gropp Rob Ross Rajeev Thakur Rob Latham
  Anthony Chan
• Northwestern University
• Alok Choudhary Wei-keng Liao Avery Ching Kenin
  Coloma Jianwei Li
• Collaborators
• Lawrence Livermore National Laboratory
• Ghaleb Abdulla Tina Eliassi-Rad Terence
  Critchlow
• Application groups

3
Focus Areas in Project

• Parallel I/O on clusters
• Parallel Virtual File System (PVFS)
• MPI-IO hints
• ROMIO MPI-IO implementation
• Grid I/O
• Linking PVFS and ROMIO with Grid I/O components
• Application interfaces
• NetCDF and HDF5
• Everything is interconnected!
• Wei-keng Liao will drill down into specific tasks

4
Parallel Virtual File System

• Lead developer R. Ross (ANL)
• R. Latham (ANL) developer
• A. Ching K. Coloma (NWU) collaborators
• Open source scalable parallel file system
• Project began in mid 90s at Clemson University
• Now a collaborative between Clemson and ANL
• Successes
• In use on large Linux clusters (OSC Utah
  Clemson ANL Phillips Petroleum )
• 100 unique downloads/month
• 160 users on mailing list 90 on developers
  list
• Multiple Gigabyte/second performance shown

5
Keeping PVFS Relevant PVFS2

• Scaling to thousands of clients and hundreds of
  servers requires some design changes
• Distributed metadata
• New storage formats
• Improved fault tolerance
• New technology new features
• High-performance networking (e.g. Infiniband
  VIA)
• Application metadata
• New design and implementation warranted (PVFS2)

6
PVFS1 PVFS2 and SDM

• Maintaining PVFS1 as a resource to community
• Providing support bug fixes
• Encouraging use by application groups
• Adding functionality to improve performance (e.g.
  tiled display)
• Implementing next-generation parallel file system
  
• Basic infrastructure for future PFS work
• New physical distributions (e.g. chunking)
• Application metadata storage
• Ensuring that a working parallel file system will
  continue to be available on clusters as they scale

7
Data Staging for Tiled Display

• Contact Joe Insley (ANL)
• Commodity components
• projectors PCs
• Provide very high resolutionvisualization
• Staging application preprocesses frames into a
  tile stream for each visualization node
• Uses MPI-IO to access data from PVFS file system
• Streams of tiles are merged into movie files on
  visualization nodes
• End goal is to display frames directly from PVFS
• Enhancing PVFS and ROMIO to improve performance

8
Example Tile Layout

• 3x2 display 6 readers
• Frame size is 2532x1408 pixels
• Tile size is 1024x768 pixels (overlapped)
• Movies broken into frames with each frame stored
  in its own file in PVFS
• Readers pull data from PVFS and send to display

9
Tested access patterns

• Subtile
• Each reader grabs a piece of a tile
• Small noncontiguous accesses
• Lots of accesses for a frame
• Tile
• Each reader grabs a whole tile
• Larger noncontiguous accesses
• Six accesses for a frame
• Reading individual pieces is simply too slow

10
Noncontiguous Access in ROMIO

• ROMIO performs data sieving to cut down number
  of I/O operations
• Uses large reads which grab multiple
  noncontiguous pieces
• Example reading tile 1

11
Noncontiguous Access in PVFS

• ROMIO data sieving
• Works for all file systems (just uses contiguous
  read)
• Reads extra data (three times desired amount)
• Noncontiguous access primitive allows requesting
  just desired bytes (A. Ching NWU)
• Support in ROMIO allowstransparent use of new
  optimization (K. ColomaNWU)
• PVFS and ROMIO supportimplemented

12
Metadata in File Systems

• Associative arrays of information related to a
  file
• Seen in other file systems (MacOS BeOS
  ReiserFS)
• Some potential uses
• Ancillary data (from applications)
• Derived values
• Thumbnail images
• Execution parameters
• I/O library metadata
• Block layout information
• Attributes on variables
• Attributes of dataset as a whole
• Headers
• Keeps header out of data stream
• Eliminates need for alignment in libraries

13
Metadata and PVFS2 Status

• Prototype metadata storage for PVFS2 implemented
• R. Ross (ANL)
• Uses Berkeley DB for storage of keyword/value
  pairs
• Need to investigate how to interface to MPI-IO
• Other components of PVFS2 coming along
• Networking in testing (P. Carns Clemson)
• Client side API under development (Clemson)
• PVFS2 beta early fourth quarter

14
ROMIO MPI-IO Implementation

• Written by R. Thakur (ANL)
• R. Ross and R. Latham (ANL) developers
• K. Coloma (NWU) collaborator
• Implementation of MPI-2 I/O specification
• Operates on wide variety of platforms
• Abstract Device Interface for I/O (ADIO) aids in
  porting to new file systems
• Successes
• Adopted by industry(e.g. Compaq HP SGI)
• Used at ASCI sites(e.g. LANL Blue Mountain)

15
ROMIO Current Directions

• Support for PVFS noncontiguous requests
• K. Coloma (NWU)
• Hints - key to efficient use of HW SW
  components
• Collective I/O
• Aggregation (synergy)
• Performance portability
• Controlling ROMIO Optimizations
• Access patterns
• Grid I/O
• Scalability
• Parallel I/O benchmarking

16
ROMIO Aggregation Hints

• Part of ASCI Software Pathforward project
• Contact Gary Grider (LANL)
• Implementation by R. Ross R. Latham (ANL)
• Hints control what processes do I/O in
  collectives
• Examples
• All processes on same node as attached storage
• One process per host
• Additionally limit number of processes who open
  file
• Good for systems w/out shared FS (e.g. O2K
  clusters)
• More scalable

17
Aggregation Example

• Cluster of SMPs
• Only one SMP box has connection to disks
• Data is aggregated to processes on single box
• Processes on that box perform I/O on behalf of
  the others

18
Optimization Hints

• MPI-IO calls should be chosen to best describe
  the I/O taking place
• Use of file views
• Collective calls for inherently collective
  operations
• Unfortunately sometimes choosing the right
  calls can result on lower performance
• Allow application programmers to tune ROMIO with
  hints rather than using different MPI-IO calls
• Avoid the misapplication of optimizations
  (aggregation data sieving)

19
Optimization Problems

• ROMIO checks for applicability of two-phase
  optimization when collective I/O is used
• With tiled display application using subtile
  access this optimization is never used
• Checking for applicability requires communication
  between processes
• Results in 33 drop in throughput (on test
  system)
• A hint that tells ROMIO not to apply the
  optimization can avoid this without changes to
  the rest of the application

20
Access Pattern Hints

• Collaboration between ANL and LLNL (and growing)
• Examining how access pattern information can be
  passed to MPI-IO interface through to underlying
  file system
• Used as input to optimizations in MPI-IO layer
• Used as input to optimizations in FS layer as
  well
• Prefetching
• Caching
• Writeback

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Status of Hints

• Aggregation control finished
• Optimization hints
• Collectives data sieving read finished
• Data sieving write control in progress
• PVFS noncontiguous I/O control in progress
• Access pattern hints
• Exchanging log files formats
• Getting up to speed on respective tools

22
Parallel I/O Benchmarking

• No common parallel I/O benchmarks
• New effort (consortium) to
• Define some terminology
• Define test methodology
• Collect tests
• Goal provide a meaningful test suite with
  consistent measurement techniques
• Interested parties at numerous sites (and
  growing)
• LLNL Sandia UIUC ANL UCAR Clemson
• In infancy

23
Grid I/O

• Looking at ways to connect our I/O work with
  components and APIs used in the Grid
• New ways of getting data in and out of PVFS
• Using MPI-IO to access data in the Grid
• Alternative mechanisms for transporting data
  across the Grid (synergy)
• Working towards more seamless integration of the
  tools used in the Grid and those used on clusters
  and in parallel applications (specifically MPI
  applications)
• Facilitate moving between Grid and Cluster worlds

24
Local Access to GridFTP Data

• Grid I/O Contact B. Allcock (ANL)
• GridFTP striped server provides high-throughput
  mechanism for moving data across Grid
• Relies on proprietary storage format on striped
  servers
• Must manage metadata on stripe location
• Data stored on servers must be read back from
  servers
• No alternative/more direct way to access local
  data
• Next version assumes shared file system underneath

25
GridFTP Striped Servers

• Remote applications connect to multiple striped
  servers to quickly transfer data over Grid
• Multiple TCP streams better utilize WAN network
• Local processes would need to use same mechanism
  to get to data on striped servers

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PVFS under GridFTP

• With PVFS underneath GridFTP servers would store
  data on PVFS I/O servers
• Stripe information stored on PVFS metadata server

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Local Data Access

• Application tasks that are part of a local
  parallel job could access data directly off PVFS
  file system
• Output from application could be retrieved
  remotely via GridFTP

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MPI-IO Access to GridFTP

• Applications such as tiled display reader desire
  remote access to GridFTP data
• Access through MPI-IO would allow this with no
  code changes
• ROMIO ADIO interface provides the infrastructure
  necessary to do this
• MPI-IO hints provide means for specifying number
  of stripes transfer sizes etc.

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WAN File Transfer Mechanism

• B. Gropp (ANL) P. Dickens (IIT)
• Applications
• PPM and COMMAS (Paul Woodward UMN)
• Alternative mechanism for moving data across Grid
  using UDP
• Focuses on requirements for file movement
• All data must arrive at destination
• Ordering doesnt matter
• Lost blocks can be retransmitted when detected
  but need not stop the remainder of the transfer

30
WAN File Transfer Performance

• Comparing TCP utilization to WAN FT technique
• See 10-12 utilization with single TCP stream (8
  streams to approach max. utilization)
• With WAN FT obtain near 90 utilization more
  uniform performance

31
Grid I/O Status

• Planning with Grid I/O group
• Matching up components
• Identifying useful hints
• Globus FTP client library is available
• 2nd generation striped server being implemented
• XIO interface prototyped
• Hooks for alternative local file systems
• Obvious match for PVFS under GridFTP

32
NetCDF

• Applications in climate and fusion
• PCM
• John Drake (ORNL)
• Weather Research and Forecast Model (WRF)
• John Michalakes (NCAR)
• Center for Extended Magnetohydrodynamic Modeling
• Steve Jardin (PPPL)
• Plasma Microturbulence Project
• Bill Nevins (LLNL)
• Maintained by Unidata Program Center
• API and file format for storing multidimensional
  datasets and associated metadata (in a single
  file)

33
NetCDF Interface

• Strong points
• Its a standard!
• I/O routines allow for subarray and strided
  access with single calls
• Access is clearly split into two modes
• Defining the datasets (define mode)
• Accessing and/or modifying the datasets (data
  mode)
• Weakness no parallel writes limited parallel
  read capability
• This forces applications to ship data to a single
  node for writing severely limiting usability in
  I/O intensive applications

34
Parallel NetCDF

• Rich I/O routines and explicit define/data modes
  provide a good foundation
• Existing applications are already describing
  noncontiguous regions
• Modes allow for a synchronization point when file
  layout changes
• Missing
• Semantics for parallel access
• Collective routines
• Option for using MPI datatypes
• Implement in terms of MPI-IO operations
• Retain file format for interoperability

35
Parallel NetCDF Status

• Design document created
• B. Gropp R. Ross and R. Thakur (ANL)
• Prototype in progress
• J. Li (NWU)
• Focus is on write functions first
• Biggest bottleneck for checkpointing applications
• Read functions follow
• Investigate alternative file formats in future
• Address differences in access modes between
  writing and reading

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FLASH Astrophysics Code

• Developed at ASCI Center at University of Chicago
• Contact Mike Zingale
• Adaptive mesh (AMR) code for simulating
  astrophysical thermonuclear flashes
• Written in Fortran90 uses MPI for communication
  HDF5 for checkpointing and visualization data
• Scales to thousands of processors runs for
  weeks needs to checkpoint
• At the time I/O was a bottleneck (½ of runtime
  on 1024 processors)

37
HDF5 Overhead Analysis

• Instrumented FLASH I/O to log calls to H5Dwrite

H5Dwrite
MPI_File_write_at
38
HDF5 Hyperslab Operations

• White region is hyperslab gather (from memory)
• Cyan is scatter (to file)

39
Hand-Coded Packing

• Packing time is in black regions between bars
• Nearly order of magnitude improvement

40
Wrap Up

• Progress being made on multiple fronts
• ANL/NWU collaboration is strong
• Collaborations with other groups maturing
• Balance of immediate payoff and medium term
  infrastructure improvements
• Providing expertise to application groups
• Adding functionality targeted at specific
  applications
• Building core infrastructure to scale ensure
  availability
• Synergy with other projects
• On to Wei-keng!