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Introduction to Message Passing Interface (MPI) Part I

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SAN DIEGO SUPERCOMPUTER CENTER. at the UNIVERSITY OF CALIFORNIA, ... TG IA-64 cluster: Based on Intel ifort & icc compilers. FORTRAN: mpif77, mpif90. C: mpicc ... – PowerPoint PPT presentation

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Title: Introduction to Message Passing Interface (MPI) Part I


1
Introduction toMessage Passing Interface
(MPI)Part I
  • SoCal Annual AAP workshop
  • October 30, 2006
  • San Diego Supercomputer Center

2
Overview
  • MPI Background and Key Concepts
  • Compilers and Include files for MPI
  • Initialization
  • Basic Communications in MPI
  • Data types
  • Summary of 6 basic MPI calls
  • Example using basic MPI calls

3
Message Passing Interface Background
  • MPI - Message Passing Interface
  • Library standard defined by committee of vendors,
    implementers, and parallel programmers
  • Used to create parallel SPMD programs based on
    message passing
  • Available on almost all parallel machines in C
    and Fortran
  • About 125 routines including advanced routines
  • 6 basic routines

4
MPI Implementations
  • Most parallel machine vendors have optimized
    versions
  • Some other popular implementations include
  • http//www-unix.mcs.anl.gov/mpi/mpich/
  • http//www.lam-mpi.org/
  • http//www.open-mpi.org/
  • http//icl.cs.utk.edu/ftmpi/
  • http//public.lanl.gov/lampi/

5
MPI Key Concepts
  • Parallel SPMD programs based on message passing.
  • Universal multiprocessor model that fits well on
    separate processors connected by fast/slow
    network.
  • Normally the same program is running on several
    different nodes.
  • Nodes communicate using message passing.
  • MP allows a way for the programmer to explicitly
    associate specific data with processes and allows
    the compiler and cache management hardware to
    function fully.

6
MPI Compilers on SDSC machines
  • DataStar Based on IBM xlf xlc compilers
  • FORTRAN mpxlf_r, mpxlf90_r, mpxlf95_r
  • C mpcc_r
  • C mpCC_r
  • Blue Gene Based on IBM xlf xlc compilers
  • FORTRAN mpxlf, mpxlf90, mpxlf95
  • C mpcc
  • C mpCC
  • TG IA-64 cluster Based on Intel ifort icc
    compilers
  • FORTRAN mpif77, mpif90
  • C mpicc
  • C mpiCC

7
MPI Include files
  • The MPI include file
  • C mpi.h
  • Fortran mpif.h (a f90 module is a good place
    for this)
  • Defines many constants used within MPI programs
  • In C defines the interfaces for the functions
  • Compilers know where to find the include files

8
Initialization
  • !ccccccccccccccccccccccccccccccccccccccccccccccccc
    ccccccccccccc!
  • ! This code illustrates the use of some basic MPI
    routines !
  • ! MPI_INIT Initialization of MPI
    !
  • ! MPI_COMM_RANK Find the ID of given task
    !
  • ! MPI_COMM_SIZE Find the total number of
    tasks !
  • ! MPI_FINALIZE Close all MPI tasks
    !
  • !ccccccccccccccccccccccccccccccccccccccccccccccccc
    ccccccccccccc!
  • PROGRAM init
  • IMPLICIT NONE
  • INCLUDE 'mpif.h'
  • INTEGER my_id, ntasks, ierr
  • CALL MPI_INIT( ierr )
  • CALL MPI_COMM_RANK( MPI_COMM_WORLD, my_id,
    ierr )
  • CALL MPI_COMM_SIZE( MPI_COMM_WORLD, ntasks,
    ierr )
  • WRITE(,) "I am task number", my_id,

9
Initialization
  • COMPILING CODE
  • ds100 mpxlf -o init initial.f
  • init End of Compilation 1
  • 1501-510 Compilation successful for file
    initial.f.
  • SUBMIT JOB
  • ds100 llsubmit LL.cmd
  • Found valid account 'USE300' for queue 'express'
  • Using ACL 'sdsc_datastarmahidharuse300sstrnp'
  • on DataStar NPACI nodes all queues
  • Job passed jobfilter
  • llsubmit Processed command file through Submit
    Filter "/users00/loadl/loadl/jobfilter-interactiv
    e.pl".
  • llsubmit The job "ds100.235768" has been
    submitted.
  • CODE OUTPUT (in ouput file)
  • 0 I am task number 0 . The total number of tasks
    is 4
  • 1 I am task number 1 . The total number of tasks
    is 4
  • 2 I am task number 2 . The total number of tasks
    is 4

10
Communicators
  • Communicators
  • A parameter for most MPI calls
  • A collection of processors working on some part
    of a parallel job
  • MPI_COMM_WORLD is defined in the MPI include file
    as all of the processors in your job
  • Can create subsets of MPI_COMM_WORLD
  • Processors within a communicator are assigned
    numbers 0 to n-1

11
Minimal MPI program
  • Every MPI program needs these
  • C version
  • Commonly Used
  • C version

include ltmpi.hgt / the mpi include file / /
Initialize MPI / ierrMPI_Init(argc, argv) /
How many total PEs are there / ierrMPI_Finalize(
)
ierrMPI_Comm_size(MPI_COMM_WORLD, nPEs) /
What node am I (what is my rank?)
/ ierrMPI_Comm_rank(MPI_COMM_WORLD, iam) ...
In C MPI routines are functions and return an
error value
12
Minimal MPI program
  • Every MPI program needs these
  • Fortran version

include 'mpif.h' ! MPI include file c
Initialize MPI call MPI_Init(ierr) c Find
total number of PEs call MPI_Comm_size(MPI_COMM_
WORLD, nPEs, ierr) c Find the rank of this
node call MPI_Comm_rank(MPI_COMM_WORLD, iam,
ierr) ... call MPI_Finalize(ierr)
In Fortran, MPI routines are subroutines, and
last parameter is an error value
13
Basic Communications in MPI
  • Data values are transferred from one processor to
    another
  • One process sends the data
  • Another receives the data
  • Standard, Blocking
  • Call does not return until the message buffer is
    free to be reused
  • Standard, Nonblocking
  • Call indicates a start of send or received, and
    another call is made to determine if finished

14
Standard, Blocking Send
  • MPI_Send Sends data to another processor
  • Use MPI_Recv to "get" the data
  • C
  • MPI_Send(buffer,count,datatype,
    destination,tag,communicator)
  • Fortran
  • Call MPI_Send(buffer, count, datatype,destination,
    tag, communicator, ierr)
  • Call blocks until message on the way

15
MPI_Send
  • Call MPI_Send(buffer, count, datatype,
    destination, tag, communicator, ierr)
  • Buffer The data
  • Count Length of source array (in elements, 1
    for scalars)
  • Datatype Type of data, for example
    MPI_DOUBLE_PRECISION, MPI_INT, etc
  • Destination Processor number of destination
    processor in communicator
  • Tag Message type (arbitrary integer)
  • Communicator Your set of processors
  • Ierr Error return (Fortran only)

16
Standard, Blocking Receive
  • Call blocks until message is in buffer
  • C
  • MPI_Recv(buffer,count, datatype, source, tag,
    communicator, status)
  • Fortran
  • Call MPI_ RECV(buffer, count, datatype,
    source,tag,communicator, status, ierr)
  • Status - contains information about incoming
    message
  • C
  • MPI_Status status
  • Fortran
  • Integer status(MPI_STATUS_SIZE)

17
Status
  • In C
  • status is a structure of type MPI_Status which
    contains three fields MPI_SOURCE, MPI_TAG, and
    MPI_ERROR
  • status.MPI_SOURCE, status.MPI_TAG, and
    status.MPI_ERROR contain the source, tag, and
    error code respectively of the received message
  • In Fortran
  • status is an array of INTEGERS of length
    MPI_STATUS_SIZE, and the 3 constants MPI_SOURCE,
    MPI_TAG, MPI_ERROR are the indices of the entries
    that store the source, tag, error
  • status(MPI_SOURCE), status(MPI_TAG),
    status(MPI_ERROR) contain respectively the
    source, the tag, and the error code of the
    received message.

18
MPI_Recv
  • Call MPI_Recv(buffer, count, datatype, source,
    tag, communicator, status, ierr)
  • Buffer The data
  • Count Max. number of elements that can be
    received
  • Datatype Type of data, for example
    MPI_DOUBLE_PRECISION, MPI_INT, etc
  • Source Processor number of source processor in
    communicator
  • Tag Message type (arbitrary integer)
  • Communicator Your set of processors
  • Status Information about message
  • Ierr Error return (Fortran only)

19
Data types
  • Data types
  • When sending a message, it is given a data type
  • Predefined types correspond to "normal" types
  • MPI_REAL , MPI_FLOAT -Fortran and C real
  • MPI_DOUBLE_PRECISION , MPI_DOUBLE - Fortan and C
    double
  • MPI_INTEGER and MPI_INT - Fortran and C integer
  • Can create user-defined types

20
Basic MPI Send and Receive
  • A parallel program to send receive data
  • Initialize MPI
  • Have processor 0 send an integer to processor 1
  • Have processor 1 receive an integer from
    processor 0
  • Both processors print the data
  • Quit MPI

21
Simple Send Receive Program
  • include ltstdio.hgt
  • include "mpi.h"
  • /
  • This is a simple send/receive program in MPI

  • /
  • int main(argc,argv)
  • int argc
  • char argv
  • int myid
  • int tag,source,destination,count
  • int buffer
  • MPI_Status status
  • MPI_Init(argc,argv)
  • MPI_Comm_rank(MPI_COMM_WORLD,myid)

22
Simple Send Receive Program (cont.)
  • tag1234
  • source0
  • destination1
  • count1
  • if(myid source)
  • buffer5678
  • MPI_Send(buffer,count,MPI_INT,destination,ta
    g,MPI_COMM_WORLD)
  • printf("processor d sent
    d\n",myid,buffer)
  • if(myid destination)
  • MPI_Recv(buffer,count,MPI_INT,source,tag,MPI_COM
    M_WORLD,status)
  • printf("processor d got
    d\n",myid,buffer)
  • MPI_Finalize()

23
Simple Send Receive Program
  • program send_recv
  • include "mpif.h
  • ! This is MPI send - recv program
  • integer myid, ierr,numprocs
  • integer tag,source,destination,count
  • integer buffer
  • integer status(MPI_STATUS_SIZE)
  • call MPI_INIT( ierr )
  • call MPI_COMM_RANK( MPI_COMM_WORLD, myid,
    ierr )
  • call MPI_COMM_SIZE( MPI_COMM_WORLD,
    numprocs, ierr )
  • tag1234
  • source0
  • destination1
  • count1

24
Simple Send Receive Program (cont.)
  • if (myid .eq. source) then
  • buffer5678
  • Call MPI_Send(buffer, count,
    MPI_INTEGER,destination,
  • tag, MPI_COMM_WORLD, ierr)
  • write(,)"processor ",myid," sent
    ",buffer
  • endif
  • if (myid .eq. destination) then
  • Call MPI_Recv(buffer, count,
    MPI_INTEGER,source,
  • tag, MPI_COMM_WORLD, status,ierr)
  • write(,)"processor ",myid," got
    ",buffer
  • endif
  • call MPI_FINALIZE(ierr)
  • stop
  • end

25
Simple Send Receive Program
  • Run the simple send receive code with 2
    processors.
  • Output
  • ds100 more LL_out.235771
  • 0 processor 0 sent 5678
  • 1 processor 1 got 5678

26
The 6 Basic MPI Calls
  • MPI is used to create parallel programs based on
    message passing
  • Usually the same program is run on multiple
    processors
  • The 6 basic calls in MPI are
  • MPI_INIT( ierr )
  • MPI_COMM_RANK( MPI_COMM_WORLD, myid, ierr )
  • MPI_COMM_SIZE( MPI_COMM_WORLD, numprocs, ierr )
  • MPI_Send(buffer, count,MPI_INTEGER,destination,
    tag, MPI_COMM_WORLD, ierr)
  • MPI_Recv(buffer, count, MPI_INTEGER,source,tag,
    MPI_COMM_WORLD, status,ierr)
  • MPI_FINALIZE(ierr)

27
Example MPI program using basic routines
  • MPI is used to create parallel programs based on
    message passing
  • Usually the same program is run on multiple
    processors
  • The 6 basic calls in MPI are
  • MPI_INIT( ierr )
  • MPI_COMM_RANK( MPI_COMM_WORLD, myid, ierr )
  • MPI_COMM_SIZE( MPI_COMM_WORLD, numprocs, ierr )
  • MPI_Send(buffer, count,MPI_INTEGER,destination,
    tag, MPI_COMM_WORLD, ierr)
  • MPI_Recv(buffer, count, MPI_INTEGER,source,tag,
    MPI_COMM_WORLD, status,ierr)
  • MPI_FINALIZE(ierr)

28
Simple Application using MPI 1-D Heat Equation
  • ?T/?t a(?2T/?x2) T(0) 0 T(1) 0 (0 x1)
  • T(x,0) is know as an initial condition.
  • Discretizing for numerical solution we get
  • T(n1)i T(n)i (a?t/?x2)(T(n)i-1-2T(n)iT(n
    )i1)
  • (n is the index in time and i is the index in
    space)
  • In this example we solve the problem using 11
    points and we distribute this problem over 3
    processors shown graphically below

29
Simple Application using MPI 1-D Heat Equation
Processor 0 Value at 0 known Get 4 from
processor 1 Solve the equation at (1,2,3) Send
3 to processor 1 Local Data Index ilocal 0 ,
1, 2, 3, 4 Global Data Index iglobal 0, 1, 2,
3, 4 Processor 1 Get 3 from processor 0 Get 7
from processor 2 Solve the equation at (4,5,6)
Send 4 to processor 0 and send 6 to processor
2 Local Data Index ilocal 0, 1, 2, 3,
4 Global Data Index iglobal 3, 4, 5, 6,
7 Processor 2 Get 6 from processor 1 Solve the
equation at (7,8,9) Value at 10 known Send 7 to
processor 1 Local Data Index ilocal 0, 1, 2,
3, 4 Global Data Index iglobal 6, 7, 8, 9, 10
30
FORTRAN CODE 1-D Heat Equation
Initial Conditions
pi
4d0datan(1d0) do ilocal 0, 4
iglobal 3my_idilocal T(0,ilocal)
dsin(pidelxdfloat(iglobal)) enddo
write(,)"Processor", my_id, "has finished
setting initial conditions"
Iterations
do itime 1 , 3 if (my_id.eq.0)
then write(,)"Running Iteration Number
", itime endif do ilocal 1, 3
T(itime,ilocal)T(itime-1,ilocal)
xalpdelt/delx/delx (T(itime-1,ilocal-1)
-2T(itime-1,ilocal)T(itime-1,ilocal1))
enddo if (my_id.eq.0) then
write(,)"Sending and receiving overlap points"
dest 1 msg_size 1
PROGRAM HEATEQN include "mpif.h"
implicit none integer iglobal, ilocal,
itime integer ierr, nnodes, my_id
integer IIM, IIK1, IIK2, IIK3, IIK4
integer dest, from, status(MPI_STATUS_SIZE),tag
integer msg_size real8
xalp,delx,delt,pi real8 T(0100,05),
TG(010) CHARACTER(20) FILEN delx
0.1d0 delt 1d-4 xalp 2.0d0
call MPI_INIT(ierr) call
MPI_COMM_SIZE(MPI_COMM_WORLD, nnodes, ierr)
call MPI_COMM_RANK(MPI_COMM_WORLD, my_id, ierr)
print , "Process ", my_id, "of", nnodes
,"has started"
31
Fortran Code 1-D Heat Equation (Contd.)
call MPI_SEND(T(itime,3),msg_size,MPI_DOUBL
E_PRECISION,dest,
tag,MPI_COMM_WORLD,ierr) endif if
(my_id.eq.1) then from 0 dest
2 msg_size 1 call
MPI_RECV(T(itime,0),msg_size,MPI_DOUBLE_PRECISION,
from, tag,MPI_COMM_WORLD,st
atus,ierr) call MPI_SEND(T(itime,3),msg_s
ize,MPI_DOUBLE_PRECISION,dest,
tag,MPI_COMM_WORLD,ierr) endif
if (my_id.eq.2) then from 1
dest 1 msg_size 1 call
MPI_RECV(T(itime,0),msg_size,MPI_DOUBLE_PRECISION,
from, tag,MPI_COMM_WORLD,st
atus,ierr) call MPI_SEND(T(itime,1),msg_s
ize,MPI_DOUBLE_PRECISION,dest,
tag,MPI_COMM_WORLD,ierr) endif
if (my_id.eq.1) then from 2
dest 0 msg_size 1
call MPI_RECV(T(itime,4),msg_size,MPI_DOUBLE_PREC
ISION,from,
tag,MPI_COMM_WORLD,status,ierr) call
MPI_SEND(T(itime,1),msg_size,MPI_DOUBLE_PRECISION,
dest, tag,MPI_COMM_WORLD,ie
rr) endif if (my_id.eq.0) then
from 1 msg_size 1 call
MPI_RECV(T(itime,4),msg_size,MPI_DOUBLE_PRECISION,
from, tag,MPI_COMM_WORLD,st
atus,ierr) endif enddo if
(my_id.eq.0) then write(,)"SOLUTION
SENT TO FILE AFTER 3 TIMESTEPS" endif
FILEN 'data'//char(my_id48)//'.dat'
open (5, fileFILEN) write(5,)"Processor
",my_id do ilocal 0 , 4 iglobal
3my_id ilocal write(5,)"ilocal",ilocal
,"iglobal",iglobal,"T",T(3,ilocal)
enddo close(5) call
MPI_FINALIZE(ierr) END
32
Simple Application using MPI 1-D Heat Equation
  • Compilation
  • Fortran mpxlf O3 heat-1d.f
  • Running Interactively on DataStar
  • Log on to dspoe.sdsc.edu
  • poe a.out nodes 1 tasks_per_node 3

33
Simple Application using MPI 1-D Heat Equation
OUTPUT FROM SAMPLE PROGRAM Process 0 of 3 has
started Processor 0 has finished
setting initial conditions Process 1 of 3
has started Processor 1 has finished
setting initial conditions Process 2
of 3 has started Processor 2 has finished
setting initial conditions
Running Iteration Number 1 Sending and
receiving overlap points Running Iteration
Number 2 Sending and receiving overlap points
Running Iteration Number 3 Sending and
receiving overlap points SOLUTION SENT TO FILE
AFTER 3 TIMESTEPS
34
Simple Application using MPI 1-D Heat Equation
ds100 more data0.dat Processor 0 ilocal 0
iglobal 0 T 0.000000000000000000E00 ilocal
1 iglobal 1 T 0.307205621017284991 ilocal 2
iglobal 2 T 0.584339815421976549 ilocal 3
iglobal 3 T 0.804274757358271253 ilocal 4
iglobal 4 T 0.945481682332597884
ds100 more data2.dat Processor 2 ilocal 0
iglobal 6 T 0.945481682332597995 ilocal 1
iglobal 7 T 0.804274757358271253 ilocal 2
iglobal 8 T 0.584339815421976660 ilocal 3
iglobal 9 T 0.307205621017285102 ilocal 4
iglobal 10 T 0.000000000000000000E00
ds100 more data1.dat Processor 1 ilocal 0
iglobal 3 T 0.804274757358271253 ilocal 1
iglobal 4 T 0.945481682332597884 ilocal 2
iglobal 5 T 0.994138272681972301 ilocal 3
iglobal 6 T 0.945481682332597995 ilocal 4
iglobal 7 T 0.804274757358271253
35
References
  • LLNL MPI tutorial
  • http//www.llnl.gov/computing/tutorials/mpi/
  • NERSC MPI tutorial
  • http//www.nersc.gov/nusers/help/tutorials/mpi/int
    ro/
  • LAM MPI tutorials
  • http//www.lam-mpi.org/tutorials/
  • Tutorial on MPI The Message-Passing Interface
  • by William Gropp
  • http//www-unix.mcs.anl.gov/mpi/tutorial/gropp/tal
    k.html
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