Dr. David Cronk Innovative Computing Lab University of ... - It works!

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MPI_SCATTERV C mnb = max number of boxes IF (MYPE .EQ. ROOT) THEN OPEN (25, FILE=‘filename’) READ (25, *) nprocs READ (25, *) (nboxes(I), I=1,nprocs) READ (25, *) mat(I,J) (I=1,nboxes(I))(J=1,nprocs) CLOSE (25) DO I = 1,nprocs displs(I) = (I-1)*mnb ENDDO ENDIF CALL MPI_SCATTER (nboxes, 1, MPI_INT, nb, 1, MPI_INT, ROOT, MPI_COMM_WORLD, ierr) CALL MPI_SCATTERV (mat, nboxes, displs, MPI_INT, lboxes, nb, MPI_INT, ROOT, MPI_COMM_WORLD, ierr) David Cronk 100
Collective Communication: Allgather MPI_ALLGATHER (sendbuf, sendcount, sendtype, recvbuf, recvcount, recvtype, comm, ierr) › Same as MPI_GATHER, except all processors get the result › MPI_IN_PLACE may be used for sendbuf of all processors › Equivalent to a gather followed by a bcast David Cronk 101
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An Introduction to Parallel Program
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Day 2 Course Outline (cont) Morning
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Day 1 Morning - Lecture Course Outl
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Parallel Processing What is paralle
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Parallel Processing David Cronk 9
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Parallel Processing Why parallel pr
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Parallel Programming Outline › Pr
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Parallel Programming Message Passin
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Data Distribution David Cronk 17
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What is MPI Introduction to MPI ›
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What is MPI A standard library spec
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Continuing to grow! What is MPI ›
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Getting Started with MPI MPI contai
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MPI_INIT (ierr) ierr: Integer error
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Basic Program Structure program mai
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MPI_COMM_RANK (comm, rank, ierr) co
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program main include ‘mpif.h’ i
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Message Passing Message passing is
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Message Passing Processes are speci
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MPI_STATUS Since a receive call onl
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Types of data parallel MPI Programs
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Peer/SPMD Example Compute the sum o
Page 49 and 50: Master/Slave Example Master code: c
Page 51 and 52: Master/Slave Example Master code: c
Page 53 and 54: Unsafe Communication Patterns send
Page 55 and 56: Jacobi Iteration Initializations .
Page 57 and 58: Day 2 Course Outline (cont) Morning
Page 59 and 60: Point-to-Point Communication Modes
Page 61 and 62: MPI_ISEND (buf, cnt, dtype, dest, t
Page 63 and 64: MPI_WAIT (request, status, ierr) Re
Page 65 and 66: MPI_WAITALL (count, requests, statu
Page 67 and 68: MPI_TESTANY (count, requests, index
Page 69 and 70: Non-blocking Communication 100 cont
Page 71 and 72: Non-blocking communication J = 0 do
Page 73 and 74: Jacobi Iteration IF (myrank .EQ. 0)
Page 75 and 76: Point-to-Point Communication Modes:
Page 77 and 78: Point-to-Point Communication Modes:
Page 79 and 80: Ready Mode SLAVE MASTER while (!don
Page 81 and 82: TAKE A BREAK David Cronk 81
Page 83 and 84: Collective Communication OUTLINE
Page 85 and 86: Collective Communication Synchroniz
Page 87 and 88: Collective Communication: Bcast MPI
Page 89 and 90: Collective Communication: Gather A
Page 91 and 92: MPI_Gather for (i = 0; i < 20; i++)
Page 93 and 94: Collective Communication: Gatherv (
Page 95 and 96: Collective Communication: Gatherv (
Page 97 and 98: MPI_SCATTER IF (MYPE .EQ. ROOT) THE
Page 99: Collective Communication: Scatterv
Page 103 and 104: Allgatherv int mycount; /* inited t
Page 105 and 106: Allgatherv p1 p2 p3 p4 MPI_Comm_ran
Page 107 and 108: Collective Communication: Alltoallv
Page 109 and 110: Example subroutine System_Change_in
Page 111 and 112: Example (cont) if (.not. rand_festk
Page 113 and 114: Collective Communication: Reduction
Page 115 and 116: MPI_REDUCE REAL a(n), b(n,m), c(m)
Page 117 and 118: MPI_ALLREDUCE REAL a(n), b(n,m), c(
Page 119 and 120: Collective Communication: Prefix Re
Page 121 and 122: Collective Communication: Reduction
Page 123 and 124: Collective Communication: Performan
Page 125 and 126: Derived Datatypes › Introduction
Page 127 and 128: Derived Datatypes (cont) Typemap =
Page 129 and 130: Datatype Constructors MPI_TYPE_DUP
Page 131 and 132: Datatype Constructors (cont) MPI_TY
Page 133 and 134: EXAMPLE REAL a(100,100), B(100,100)
Page 139 and 140: MPI_TYPE_CREATE_STRUCT int i; char
Page 141 and 142: MPI_TYPE_CREATE_RESIZED Struct s1 {
Page 145 and 146: Datatype Constructors: Subarrays (1
Page 147 and 148: Datatype Constructors (cont) Derive
Page 149 and 150: int i; char c[100]; MPI_Aint disp[2
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TAKE A BREAK David Cronk 151
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Communicators and Groups Many MPI u
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Communicators and Groups(cont) P 2
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Group Management You can access inf
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Course Outline (cont) Day 3 Morning
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One Sided Communication By requirin
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One Sided Communication Get Put Add
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One Sided Communication Data moveme
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Dynamic Process Management Spawning
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MPI-I/O Introduction › What is pa
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What is parallel I/O INTRODUCTION
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What is parallel I/O INTRODUCTION
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INTRODUCTION (cont) Integer dim par
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INTRODUCTION (cont) Why use paralle
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INTRODUCTION (cont) What is MPI-I/O
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Recommended references MPI - The Co
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