MPI MPI. Linux. Linux. Message Passing Interface. Message Passing Interface. August 14, August 14, 2007 MPICH. MPI MPI Send Recv MPI

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1 Linux MPI Linux MPI Message Passing Interface Linux MPI Linux MPI Message Passing Interface MPI MPICH MPI Department of Science and Engineering Computing School of Mathematics School Peking University MPI MPICH MPI Department of Science and Engineering Computing School of Mathematics School Peking University August 14, 2007 August 14, 2007 MPI Linux MPI 1 MPI Linux MPI MPI MPICH MPI 2 MPICH MPICH 3 MPI MPI MPI Send Recv MPI MPI MPI MPICH MPI MPIMPICH, LAM-MPI MPI 4

2 MPICH Ubuntu, Suse, Fedora Core Linux MPI Linux MPI MPI MPICH MPICH MPI./configure make make install rshmpich MPI MPICH MPICH MPI : mpich, MPICH I MPICH II Linux MPI MPI MPICH MPICH MPI mpdboot mpdboot_pku-desktop (handle_mpd_output 388): from mpd on pku-desktop, invalid port info: mpd failed: gethostbyname_ex failed for pku-desktop 1. hosts cat /etc/hosts : localhost pku-desktop.tiao-1482 Linux MPI MPI MPICH MPICH MPI tlu@pku-desktop:~$ /sbin/ifconfig eth0 : xx:1xx:xx:xx:xx:xx inet : xx.xxx : : inet IP 3. /etc/hosts : xx.xxx pkudesktop pku-desktop IP, pku-desktop mpd failed: gethostbyname_ex failed for pku-desktop ; localhost pku-desktop.tiao xx.xxx pku-desktop pku-desktop 2. ip 4. mpdboot,

3 MPI C++ MPI C++ Linux MPI MPI MPICH MPICH MPI #include "mpi.h" #include <iostream> int main(int argc, char * argv[]){ int rank; int size; MPI_Init(&argc,&argv); MPI_Comm_rank(MPI_COMM_WORLD, &rank); MPI_Comm_size(MPI_COMM_WORLD, &size); std::cout<<"hello world from process "; std::cout<rank<<" of "<<size<<std::endl; MPI_Finalize(); return 0; } Linux MPI MPI MPICH MPICH MPI mpicxx -o hello.out hello.cpp mpdboot touch ~/.mpd.conf chmod 600.mpd.conf mpdboot node mpirun -n 2./hello.out Hello world from process 0 of 2 Hello world from process 1 of 2 mpdcleanup MPI Communicator Linux MPI Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI MPI MPI (rank) MPI MPICH MPI MPI MPI Send Recv MPI MPI (intra-communicator) (inter-communicator) MPI_COMM_WORLD MPI_COMM_SELF

4 MPI C Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI MPI CMPI_Xxxxx MPI Fortran C Fortan C int myrank; MPI_Comm_rank(MPI_COMM_WORLD, &myrank) INTEGER MYRANK, IERR Call MPI_Comm_rank(MPI_COMM_WORLD, MYRANK, IERR) Fortan C MPI_Xxxx Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI MPI_Init MPI_Comm_size MPI_Comm_rank copy MPI_Finalize(); MPI Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI Note, Hello world from process 0 of 2 Hello world from process 1 of 2, It is at this point that we want to make a critical observation: when running with MPI, all processes use the same compiled binary, and hence all processes are running the exact same code. What in an MPI distinguishes a parallel program running on P processors from the serial version of the code running on P processors? Two things distinguish the parallel program: Each process uses its process rank to determine what part of the algorithm instructions are meant for it. Processes communicate with each other in order to accomplish the final task. Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI MPI6 : MPI_Init MPI_Finalize MPI_Comm_Rank MPI_Comm_Size MPI_Send MPI_Recv

5 Linux MPI Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI IN comm () OUT rank comm int MPI_Comm_rank(MPI_Comm comm, int *rank) MPI MPICH MPI MPI MPI Send Recv MPI IN comm () OUT size comm int MPI_Comm_size(MPI_Comm comm, int *size) MPI MPI Linux MPI Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI IN buf () IN count () IN datatype () IN dest () IN tag () IN comm () int MPI_Send( void* buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Commcomm) MPI MPICH MPI MPI MPI Send Recv MPI MPI_Sendcount( )datatype desttag datatypempi MPI MPI

6 Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI OUT buf ( ) IN count () IN datatype () IN source () IN tag () IN comm ( ) OUT status () int MPI_Recv(void* buf, int count, MPI_Datatype datatype, int source, int tag,mpi_comm comm, MPI_Status *status) Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI source datatypetag countmpi count Send Recv Send Recv Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI int mynode, totalnodes; int datasize; // number of data units to be sent/recv int sender; // process number of the sending process int receiver; // process number of the receiving process int tag; // integer message tag MPI_Status status; // variable to contain status information MPI_Init(&argc,&argv); MPI_Comm_size(MPI_COMM_WORLD, &totalnodes); MPI_Comm_rank(MPI_COMM_WORLD, &mynode); // Determine datasize double * databuffer = new double[datasize]; // Fill in sender, receiver, tag on sender/receiver processes, // and fill in databuffer on the sender process. Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI if(mynode==sender) MPI_Send(databuffer,datasize,MPI_DOUBLE,receiver, tag,mpi_comm_world); if(mynode==receiver) MPI_Recv(databuffer,datasize,MPI_DOUBLE,sender,tag, MPI_COMM_WORLD,&status); // Send/Recv complete

7 Remarks on Send/Recv 1,2,3,...,1000 Linux MPI Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI In general, the message array for both the sender and receiver should be of the same type and both of size at least datasize. In most cases the sendtype and recvtype are identical. The tag can be any integer between MPI MPICH MPI MPI MPI Send Recv MPI MPI #include <iostream> using namespace std; int main(int argc, char ** argv){ int sum; sum = 0; for(int i=1;i<=1000;i=i+1) sum = sum + i; cout << "The sum from 1 to 1000 is: " << sum << endl; } 1,2,3,...,1000 Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI : P1000? (by using MPI_Comm_size and MPI_Comm_rankrespectively) MyPID NumProc NumProc1000, startval = 1000*MyPID/NumProc + 1; endval = 1000*(MyPID+1)/NumProc; NumProc = 2 Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI Processor 1000/NumProc : sum = (startval + + endval) Process 0 process sum Send Process 0 Process 0 Recv Process sumprocess 0 accum Processsum = sum + accum

8 I II Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI #include<iostream> #include<mpi.h> using namespace std; int main(int argc, char ** argv){ int mynode, totalnodes; int sum,startval,endval,accum; MPI_Status status; MPI_Init(argc,argv); // MPI_Comm_size(MPI_COMM_WORLD, &totalnodes); // MPI_Comm_rank(MPI_COMM_WORLD, &mynode); Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI sum = 0; // zero sum for accumulation startval = 1000*mynode/totalnodes+1; endval = 1000*(mynode+1)/totalnodes; for(int i=startval;i<=endval;i=i+1) sum = sum + i; if(mynode!=0) MPI_Send(&sum,1,MPI_INT,0,1,MPI_COMM_WORLD); else for(int j=1;j<totalnodes;j=j+1){ MPI_Recv(&accum,1,MPI_INT,j,1, MPI_COMM_WORLD, &status); sum = sum + accum; } III comments on the code Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI } if(mynode == 0) cout << "The sum from 1 to 1000 is: " << sum << endl; MPI_Finalize(); Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI MPI observe that there is an if statement, which distinguishes between whether you are process 0 or any other process. Why? Because recall, all processes other than process zero are sending, whereas process 0 is receiving. We should decide our programs so that for each message sent using an the command MPI Send, there is some receiving process. Hence, whereas each process other than 0 has one MPI Send call, process 0 has (NumProc-1) MPI Recv calls. This is an important concept to understand. Often times an MPI program has been sitting idle because one process was sending, and there were no process waiting to receive! you are not expected to to go out and write MPI codes using sends and receives with blinding efficiency. You will learn more and gather enough confidence to write an efficient MPI code.

9 MPI MPI Linux MPI MPI MPICH MPI MPI MPI MPI Linux MPI MPI MPICH MPI MPI (a) C MPI MPI_INT MPI_FLOAT MPI_DOUBLE MPI_CHAR MPI_BYTE MPI_PACKED. C int float double char byte. MPI Send Recv MPI MPI MPI Send Recv MPI MPI (b) FORTRAN 77 MPI MPI_INTEGER MPI_REAL MPI_DOUBLE_PRECISION MPI_COMPLEX MPI_DOUBLE_COMPLEX. C INTEGER REAL DOUBLE PRECISION COMPLEX DOUBLE COMPLEX. Linux MPI Linux MPI MPI MPICH MPI MPI MPI Send Recv MPI 1 (blocking) 2 (non blocking) 1 (standard mode) 2 (buffered mode) 3 (synchronous mode) 4 (ready mode) MPI MPICH MPI MPI MPI Send Recv MPI MPI MPI

10 MPI Linux MPI Linux MPI MPI MPICH MPI MPI MPI MPI MPICH MPI MPI MPI SPMD MPMD Send Recv Send Recv MPI MPI MPI MPI I II Linux MPI MPI MPICH MPI 1 (a) mainmaster 0-1 (b) Modify the MPI Send/MPI Recv sequence such that all processes except master send, and process master receives. (Hint: From the example, in the MPI Send, the 0, denotes that you are sending to process zero; in the MPI Recv, the j denotes the process from which a message is being received. These will need to be modified.) (c) Output the sum from master. (d) Add cout statements so that each sending process prints a message stating to whom it is sending, and add cout statements so that the receiving process acknowledges from whom it has received. 2 Modify the summing example as follows: Linux MPI MPI MPICH MPI (a) Instead of summing integers, change the appropriate variables so that you will now sum doubles. You will need to use MPI_DOUBLE instead of MPI_INT within the MPI calls. Verify that you obtain the same answer as the integer case. (b) Change the sum so that you are summing 1/i instead of i. (c) Add the following line: cout.precision(20); After making these changes and recompiling, run your program on 2,4, and 8 processes. What differences in the sum of 1/i do you see? Postulate as to why this is so. 3 Modify the parallel MPI code to do the following: (a) Have process zero query the user for the number of elements over which to sum. (b) From process zero, distribute to all processes the number of elements to sum (using sends and receives) and appropriately calculate the interval over which each process is to sum. (c) Accomplish the summing as is already done in the program.

11 III Linux MPI MPI MPICH (d) After creating the final answer on process zero, print the result. MPI