Csci 4320 6360 parallel programming computing tues fri 12 1 30 p m mpi file i o
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CSCI-4320/6360: Parallel Programming & Computing Tues./Fri. 12-1:30 p.m. MPI File I/O PowerPoint PPT Presentation


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Prof. Chris Carothers Computer Science Department MRC 309a [email protected] www.cs.rpi.edu/~chrisc/COURSES/PARALLEL/SPRING-2013 Adapted from: people.cs.uchicago.edu/~asiegel/courses/cspp51085/.../mpi-io.ppt.

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CSCI-4320/6360: Parallel Programming & Computing Tues./Fri. 12-1:30 p.m. MPI File I/O

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Csci 4320 6360 parallel programming computing tues fri 12 1 30 p m mpi file i o

PPC 2013 - MPI Parallel File I/O

Prof. Chris Carothers

Computer Science Department

MRC 309a

[email protected]

www.cs.rpi.edu/~chrisc/COURSES/PARALLEL/SPRING-2013

Adapted from: people.cs.uchicago.edu/~asiegel/courses/cspp51085/.../mpi-io.ppt

CSCI-4320/6360: Parallel Programming & ComputingTues./Fri. 12-1:30 p.m.MPI File I/O


Common ways of doing i o in parallel programs

PPC 2013 - MPI Parallel File I/O

Common Ways of Doing I/O in Parallel Programs

  • Sequential I/O:

    • All processes send data to rank 0, and 0 writes it to the file


Pros and cons of sequential i o

PPC 2013 - MPI Parallel File I/O

Pros and Cons of Sequential I/O

  • Pros:

    • parallel machine may support I/O from only one process (e.g., no common file system)

    • Some I/O libraries (e.g. HDF-4, NetCDF, PMPIO) not parallel

    • resulting single file is handy for ftp, mv

    • big blocks improve performance

    • short distance from original, serial code

  • Cons:

    • lack of parallelism limits scalability, performance (single node bottleneck)


Another way

PPC 2013 - MPI Parallel File I/O

Another Way

  • Each process writes to a separate file

  • Pros:

    • parallelism, high performance

  • Cons:

    • lots of small files to manage

    • LOTS OF METADATA – stress parallel filesystem

    • difficult to read back data from different number of processes


What is parallel i o

PPC 2013 - MPI Parallel File I/O

What is Parallel I/O?

  • Multiple processes of a parallel program accessing data (reading or writing) from a common file

FILE

P(n-1)

P0

P1

P2


Why parallel i o

PPC 2013 - MPI Parallel File I/O

Why Parallel I/O?

  • Non-parallel I/O is simple but

    • Poor performance (single process writes to one file) or

    • Awkward and not interoperable with other tools (each process writes a separate file)

  • Parallel I/O

    • Provides high performance

    • Can provide a single file that can be used with other tools (such as visualization programs)


Why is mpi a good setting for parallel i o

PPC 2013 - MPI Parallel File I/O

Why is MPI a Good Setting for Parallel I/O?

  • Writing is like sending a message and reading is like receiving.

  • Any parallel I/O system will need a mechanism to

    • define collective operations (MPI communicators)

    • define noncontiguous data layout in memory and file (MPI datatypes)

    • Test completion of nonblocking operations (MPI request objects)

  • i.e., lots of MPI-like machinery


Mpi io background

PPC 2013 - MPI Parallel File I/O

MPI-IO Background

  • Marc Snir et al (IBM Watson) paper exploring MPI as context for parallel I/O (1994)

  • MPI-IO email discussion group led by J.-P. Prost (IBM) and Bill Nitzberg (NASA), 1994

  • MPI-IO group joins MPI Forum in June 1996

  • MPI-2 standard released in July 1997

  • MPI-IO is Chapter 9 of MPI-2


Using mpi for simple i o

PPC 2013 - MPI Parallel File I/O

FILE

P(n-1)

P0

P1

P2

Using MPI for Simple I/O

Each process needs to read a chunk of data from a common file


Using individual file pointers

PPC 2013 - MPI Parallel File I/O

Using Individual File Pointers

#include<stdio.h>

#include<stdlib.h>

#include "mpi.h"

#define FILESIZE 1000

int main(int argc, char **argv){

int rank, nprocs;

MPI_File fh;

MPI_Status status;

int bufsize, nints;

int buf[FILESIZE];

MPI_Init(&argc, &argv);

MPI_Comm_rank(MPI_COMM_WORLD, &rank);

MPI_Comm_size(MPI_COMM_WORLD, &nprocs);

bufsize = FILESIZE/nprocs;

nints = bufsize/sizeof(int);

MPI_File_open(MPI_COMM_WORLD, "datafile",

MPI_MODE_RDONLY, MPI_INFO_NULL, &fh);

MPI_File_seek(fh, rank * bufsize, MPI_SEEK_SET);

MPI_File_read(fh, buf, nints, MPI_INT, &status);

MPI_File_close(&fh);

}


Using explicit offsets

PPC 2013 - MPI Parallel File I/O

Using Explicit Offsets

#include<stdio.h>

#include<stdlib.h>

#include "mpi.h"

#define FILESIZE 1000

int main(int argc, char **argv){

int rank, nprocs;

MPI_File fh;

MPI_Status status;

int bufsize, nints;

int buf[FILESIZE];

MPI_Init(&argc, &argv);

MPI_Comm_rank(MPI_COMM_WORLD, &rank);

MPI_Comm_size(MPI_COMM_WORLD, &nprocs);

bufsize = FILESIZE/nprocs;

nints = bufsize/sizeof(int);

MPI_File_open(MPI_COMM_WORLD, "datafile", MPI_MODE_RDONLY, MPI_INFO_NULL, &fh);

MPI_File_read_at(fh, rank*bufsize, buf, nints, MPI_INT, &status);

MPI_File_close(&fh);

}


Function details

PPC 2013 - MPI Parallel File I/O

Function Details

MPI_File_open(MPI_Comm comm, char *file, int mode, MPI_Info info, MPI_File *fh)

(note: mode = MPI_MODE_RDONLY, MPI_MODE_RDWR, MPI_MODE_WRONLY,

MPI_MODE_CREATE, MPI_MODE_EXCL,

MPI_MODE_DELETE_ON_CLOSE, MPI_MODE_UNIQUE_OPEN,

MPI_MODE_SEQUENTIAL, MPI_MODE_APPEND)

MPI_File_close(MPI_File *fh)

MPI_File_read(MPI_File fh, void *buf, int count, MPI_Datatype type, MPI_Status *status)

MPI_File_read_at(MPI_File fh, int offset, void *buf, int count,

MPI_Datatype type, MPI_Status *status)

MPI_File_seek(MPI_File fh, MPI_Offset offset, in whence);

(note: whence = MPI_SEEK_SET, MPI_SEEK_CUR, or MPI_SEEK_END)

MPI_File_write(MPI_File fh, void *buf, int count, MPI_Datatype datatype, MPI_Status *status)

MPI_File_write_at( …same as read_at … );

(Note: Many other functions to get/set properties (see Gropp et al))


Writing to a file

PPC 2013 - MPI Parallel File I/O

Writing to a File

  • Use MPI_File_write or MPI_File_write_at

  • Use MPI_MODE_WRONLY or MPI_MODE_RDWR as the flags to MPI_File_open

  • If the file doesn’t exist previously, the flag MPI_MODE_CREATE must also be passed to MPI_File_open

  • We can pass multiple flags by using bitwise-or ‘|’ in C, or addition ‘+” in Fortran


Mpi datatype interlude

PPC 2013 - MPI Parallel File I/O

MPI Datatype Interlude

  • Datatypes in MPI

    • Elementary: MPI_INT, MPI_DOUBLE, etc

      • everything we’ve used to this point

  • Contiguous

    • Next easiest: sequences of elementary types

  • Vector

    • Sequences separated by a constant “stride”


Mpi datatypes cont

PPC 2013 - MPI Parallel File I/O

MPI Datatypes, cont

  • Indexed: more general

    • does not assume a constant stride

  • Struct

    • General mixed types (like C structs)


Creating simple datatypes

PPC 2013 - MPI Parallel File I/O

Creating simple datatypes

  • Let’s just look at the simplest types: contiguous and vector datatypes.

  • Contiguous example

    • Let’s create a new datatype which is two ints side by side. The calling sequence is

      MPI_Type_contiguous(int count, MPI_Datatype oldtype, MPI_Datatype *newtype);

      MPI_Datatype newtype;

      MPI_Type_contiguous(2, MPI_INT, &newtype);

      MPI_Type_commit(newtype); /* required */


Using file views

PPC 2013 - MPI Parallel File I/O

Using File Views

  • Processes write to shared file

  • MPI_File_set_view assigns regions of the file to separate processes


File views

PPC 2013 - MPI Parallel File I/O

File Views

  • Specified by a triplet (displacement, etype, and filetype) passed to MPI_File_set_view

  • displacement = number of bytes to be skipped from the start of the file

  • etype = basic unit of data access (can be any basic or derived datatype)

  • filetype = specifies which portion of the file is visible to the process

  • This is a collective operation and so all processors/ranks must use the same data rep, etypes in the group determined when the file was open..


File interoperability

PPC 2013 - MPI Parallel File I/O

File Interoperability

  • Users can optionally create files with a portable binary data representation

  • “datarep” parameter to MPI_File_set_view

  • native -default, same as in memory, not portable

  • internal - impl. defined representation providing an impl. defined level of portability

  • external32 - a specific representation defined in MPI, (basically 32-bit big-endian IEEE format), portable across machines and MPI implementations


File view example

PPC 2013 - MPI Parallel File I/O

File View Example

MPI_File thefile;

for (i=0; i<BUFSIZE; i++)

buf[i] = myrank * BUFSIZE + i;

MPI_File_open(MPI_COMM_WORLD, "testfile",

MPI_MODE_CREATE | MPI_MODE_WRONLY,

MPI_INFO_NULL, &thefile);

MPI_File_set_view(thefile, myrank * BUFSIZE,

MPI_INT, MPI_INT, "native",

MPI_INFO_NULL);

MPI_File_write(thefile, buf, BUFSIZE, MPI_INT,

MPI_STATUS_IGNORE);

MPI_File_close(&thefile);


Ways to write to a shared file

PPC 2013 - MPI Parallel File I/O

Ways to Write to a Shared File

like Unix seek

  • MPI_File_seek

  • MPI_File_read_at

  • MPI_File_write_at

  • MPI_File_read_shared

  • MPI_File_write_shared

  • Collective operations

combine seek and I/O

for thread safety

use shared file pointer

good when order

doesn’t matter


Collective i o in mpi

PPC 2013 - MPI Parallel File I/O

Collective I/O in MPI

  • A critical optimization in parallel I/O

  • Allows communication of “big picture” to file system

  • Framework for 2-phase I/O, in which communication precedes I/O (can use MPI machinery)

  • Basic idea: build large blocks, so that reads/writes in I/O system will be large

Small individual

requests

Large collective

access


Collective i o

PPC 2013 - MPI Parallel File I/O

Collective I/O

  • MPI_File_read_all, MPI_File_read_at_all, etc

  • _all indicates that all processes in the group specified by the communicator passed to MPI_File_open will call this function

  • Each process specifies only its own access information -- the argument list is the same as for the non-collective functions


Collective i o1

PPC 2013 - MPI Parallel File I/O

Collective I/O

  • By calling the collective I/O functions, the user allows an implementation to optimize the request based on the combined request of all processes

  • The implementation can merge the requests of different processes and service the merged request efficiently

  • Particularly effective when the accesses of different processes are noncontiguous and interleaved


Collective non contiguous mpi io examples

PPC 2013 - MPI Parallel File I/O

Collective non-contiguousMPI-IO examples

#define “mpi.h”

#define FILESIZE 1048576

#define INTS_PER_BLK 16

int main(int argc, char **argv){

int *buf, rank, nprocs, nints, bufsize;

MPI_File fh;

MPI_Datatype filetype;

MPI_Init(&argc, &argv);

MPI_Comm_rank(MPI_COMM_WORLD, &rank);

MPI_Comm_size(MPI_COMM_WORLD, &nprocs);

bufsize = FILESIZE/nprocs;

buf = (int *) malloc(bufsize);

nints = bufsize/sizeof(int);

MPI_File_open(MPI_COMM_WORLD, “filename”, MPI_MODE_RD_ONLY, MPI_INFO_NULL, &fh);

MPI_Type_vector(nints/INTS_PER_BLK, INTS_PER_BLK, INTS_PER_BLK*nprocs, MPI_INT, &filetype);

MPI_Type_commit(&filetype);

MPI_File_set_view(fh, INTS_PER_BLK*sizeof(int)*rank, MPI_INT, filetype, “native”, MPI_INFO_NULL);

MPI_File_read_all(fh, buf, nints, MPI_INT, MPI_STATUS_IGNORE);

MPI_Type_free(&filetype);

free(buf)

MPI_Finalize();

return(0);

}


More on mpi read all

PPC 2013 - MPI Parallel File I/O

More on MPI_Read_all

  • Note that the _all version has the same argument list

  • Difference is that all processes involved in MPI_Open must call this the read

  • Contrast with the non-all version where any subset may or may not call it

  • Allows for many optimizations


Split collective i o

PPC 2013 - MPI Parallel File I/O

Split Collective I/O

  • A restricted form of nonblocking collective I/O

  • Only one active nonblocking collective operation allowed at a time on a file handle

  • Therefore, no request object necessary

MPI_File_write_all_begin(fh, buf, count, datatype);

// available on Blue Gene/L, but may not improve

// performance

for (i=0; i<1000; i++) {

/* perform computation */

}

MPI_File_write_all_end(fh, buf, &status);


Passing hints to the implementation

PPC 2013 - MPI Parallel File I/O

Passing Hints to the Implementation

MPI_Info info;

MPI_Info_create(&info);

/* no. of I/O devices to be used for file striping */

MPI_Info_set(info, "striping_factor", "4");

/* the striping unit in bytes */

MPI_Info_set(info, "striping_unit", "65536");

MPI_File_open(MPI_COMM_WORLD, "/pfs/datafile",

MPI_MODE_CREATE | MPI_MODE_RDWR, info, &fh);

MPI_Info_free(&info);


Examples of hints used in romio

PPC 2013 - MPI Parallel File I/O

Examples of Hints (used in ROMIO)

  • striping_unit

  • striping_factor

  • cb_buffer_size

  • cb_nodes

  • ind_rd_buffer_size

  • ind_wr_buffer_size

  • start_iodevice

  • pfs_svr_buf

  • direct_read

  • direct_write

MPI-2 predefined hints

New Algorithm Parameters

Platform-specific hints


I o consistency semantics

PPC 2013 - MPI Parallel File I/O

I/O Consistency Semantics

  • The consistency semantics specify the results when multiple processes access a common file and one or more processes write to the file

  • MPI guarantees stronger consistency semantics if the communicator used to open the file accurately specifies all the processes that are accessing the file, and weaker semantics if not

  • The user can take steps to ensure consistency when MPI does not automatically do so


Example 1

PPC 2013 - MPI Parallel File I/O

Process 0

Process 1

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=0,cnt=100)

MPI_File_read_at(off=0,cnt=100)

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=100,cnt=100)

MPI_File_read_at(off=100,cnt=100)

Example 1

  • File opened with MPI_COMM_WORLD. Each process writes to a separate region of the file and reads back only what it wrote.

  • MPI guarantees that the data will be read correctly


Example 2

PPC 2013 - MPI Parallel File I/O

Example 2

  • Same as example 1, except that each process wants to read what the other process wrote (overlapping accesses)

  • In this case, MPI does not guarantee that the data will automatically be read correctly

Process 0

Process 1

/* incorrect program */

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=0,cnt=100)

MPI_Barrier

MPI_File_read_at(off=100,cnt=100)

/* incorrect program */

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=100,cnt=100)

MPI_Barrier

MPI_File_read_at(off=0,cnt=100)

  • In the above program, the read on each process is not guaranteed to get the data written by the other process!


Example 2 contd

PPC 2013 - MPI Parallel File I/O

Example 2 contd.

  • The user must take extra steps to ensure correctness

  • There are three choices:

    • set atomicity to true

    • close the file and reopen it

    • ensure that no write sequence on any process is concurrent with any sequence (read or write) on another process/MPI rank

      • Can hurt performance….


Example 2 option 1 set atomicity to true

PPC 2013 - MPI Parallel File I/O

Process 0

Process 1

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_set_atomicity(fh1,1)

MPI_File_write_at(off=0,cnt=100)

MPI_Barrier

MPI_File_read_at(off=100,cnt=100)

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_set_atomicity(fh2,1)

MPI_File_write_at(off=100,cnt=100)

MPI_Barrier

MPI_File_read_at(off=0,cnt=100)

Example 2, Option 1Set atomicity to true


Example 2 option 2 close and reopen file

PPC 2013 - MPI Parallel File I/O

Example 2, Option 2Close and reopen file

Process 0

Process 1

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=0,cnt=100)

MPI_File_close

MPI_Barrier

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_read_at(off=100,cnt=100)

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=100,cnt=100)

MPI_File_close

MPI_Barrier

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_read_at(off=0,cnt=100)


Example 2 option 3

PPC 2013 - MPI Parallel File I/O

Example 2, Option 3

  • Ensure that no write sequence on any process is concurrent with any sequence (read or write) on another process

  • a sequence is a set of operations between any pair of open, close, or file_sync functions

  • a write sequence is a sequence in which any of the functions is a write operation


Example 2 option 31

PPC 2013 - MPI Parallel File I/O

Process 0

Process 1

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_write_at(off=0,cnt=100)

MPI_File_sync

MPI_Barrier

MPI_File_sync /*collective*/

MPI_File_sync /*collective*/

MPI_Barrier

MPI_File_sync

MPI_File_read_at(off=100,cnt=100)

MPI_File_close

MPI_File_open(MPI_COMM_WORLD,…)

MPI_File_sync /*collective*/

MPI_Barrier

MPI_File_sync

MPI_File_write_at(off=100,cnt=100)

MPI_File_sync

MPI_Barrier

MPI_File_sync /*collective*/

MPI_File_read_at(off=0,cnt=100)

MPI_File_close

Example 2, Option 3


General guidelines for achieving high i o performance

PPC 2013 - MPI Parallel File I/O

General Guidelines for Achieving High I/O Performance

  • Buy sufficient I/O hardware for the machine

  • Use fast file systems, not NFS-mounted home directories

  • Do not perform I/O from one process only

  • Make large requests wherever possible

  • For noncontiguous requests, use derived datatypes and a single collective I/O call


Optimizations

PPC 2013 - MPI Parallel File I/O

Optimizations

  • Given complete access information, an implementation can perform optimizations such as:

    • Data Sieving: Read large chunks and extract what is really needed

    • Collective I/O: Merge requests of different processes into larger requests

    • Improved prefetching and caching


Summary

PPC 2013 - MPI Parallel File I/O

Summary

  • MPI-IO has many features that can help users achieve high performance

  • The most important of these features are the ability to specify noncontiguous accesses, the collective I/O functions, and the ability to pass hints to the implementation

  • Users must use the above features!

  • In particular, when accesses are noncontiguous, users must create derived datatypes, define file views, and use the collective I/O functions


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