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    Lab Manual 07 - P&DC

    Uploaded by

    Nitasha Huma
    This lab focuses on advanced MPI communication including sending and receiving arrays and simultaneous send and receive operations. Key points include using non-overlapping memory regions for send and receive, using tags to distinguish messages, and that receive order is not guaranteed. The example program initializes an array on process 0 and sends it to other processes using MPI_Send and MPI_Recv. Simultaneous send and receive uses MPI_Sendrecv to exchange messages in one operation.

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    Lab Manual 07 - P&DC

    Uploaded by

    Nitasha Huma
    14 views3 pages
    This lab focuses on advanced MPI communication including sending and receiving arrays and simultaneous send and receive operations. Key points include using non-overlapping memory regions for send and receive, using tags to distinguish messages, and that receive order is not guaranteed. The example program initializes an array on process 0 and sends it to other processes using MPI_Send and MPI_Recv. Simultaneous send and receive uses MPI_Sendrecv to exchange messages in one operation.

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    This lab focuses on advanced MPI communication including sending and receiving arrays and simultaneous send and receive operations. Key points include using non-overlapping memory regions for send and receive, using tags to distinguish messages, and that receive order is not guaranteed. The example program initializes an array on process 0 and sends it to other processes using MPI_Send and MPI_Recv. Simultaneous send and receive uses MPI_Sendrecv to exchange messages in one operation.

    Copyright:

    © All Rights Reserved
    Download as DOCX, PDF, TXT or read online from Scribd
    Download as docx, pdf, or txt
    14 views3 pages

    Lab Manual 07 - P&DC

    Uploaded by

    Nitasha Huma
    This lab focuses on advanced MPI communication including sending and receiving arrays and simultaneous send and receive operations. Key points include using non-overlapping memory regions for send and receive, using tags to distinguish messages, and that receive order is not guaranteed. The example program initializes an array on process 0 and sends it to other processes using MPI_Send and MPI_Recv. Simultaneous send and receive uses MPI_Sendrecv to exchange messages in one operation.

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    © All Rights Reserved
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    Download as docx, pdf, or txt
    of 3

    Lab # 7 – Parallel & Distributed Computing (CPE-421)

    Lab Manual # 7

    Objective:
    To study the advance communication between MPI processes

    Theory:
    This Lab session will focus on more information about se4nding and receiving in MPI
    like sending of arrays and simultaneous send and receive

    Key Points:

     Whenever you send and receive data, MPI assumes that you have provided non
    overlapping positions in memory. As discussed in the previous lab session,
    MPI_COMM_WORLD is referred to as a communicator. In general, a communicator is a
    collection of processes that can send messages to each other. MPI_COMM_WORLD is
    pre-defined in all implementations of MPI, and it consists of all MPI processes
    running after the initial execution of the program.
     In the send/receive, we are required to use a tag. The tag variable is used to
    distinguish upon receipt between two messages sent by the same process.
     The order of sending does not necessarily guarantee the order of receiving. Tags are
    used to distinguish between messages. MPI allows the tag MPI_ANY_TAG which can
    be used by MPI_Recvto accept any valid tag from a sender but you cannot use
    MPI_ANY_TAG in the MPI_Send command.
     Similar to the MPI_ ANY_ TAG wildcard for tags, there is also an MPI_ANY_SOURCE
    wildcard that can also be used by MPI_Recv. By using it in an MPI_Recv, a process
    is ready to receive from any sending process. Again, you cannot use MPI_ ANY_
    SOURCE in the MPI_ Send command. There is no wildcard for senderdestinations.
     When you pass an array to MPI_ Send/MPI_Recv, it need not have exactly the
    number of items to be sent. It must have greater than or equal to the number of items
    to be sent. Suppose, for example, that you had an array of 100 items, but you only
    wanted to send the first ten items, you can do so by passing the array to
    MPI_Sendand only stating that ten items are to be sent.

    An Example Program:

    In the following MPI code, array on each process is created, initialize it on process 0.
    Once the array has been initialized on process 0, then it is sent out to each process.

    Raheel Amjad 2018-CPE-07


    Lab # 7 – Parallel & Distributed Computing (CPE-421)

    Key Points:

     An array is created, on each process, using dynamic memoryallocation.


     On process 0 only (i.e., mynode == 0), an array is initialized to contain the ascending
    indexvalues.
     On process 0, program proceeds with (totalnodes-1) calls to MPISend.
     On all other processes other than 0, MPI_Recv is called to receive thesent message.
     On each individual process, the results are printed of the sending/receivingpair.

    Simultaneous Send and Receive, MPI_Sendrecv:

    The subroutine MPI_Sendrecv exchanges messages with another process. A send-


    receive operation is useful for avoiding some kinds of unsafe interaction patterns and for
    implementing remote procedure calls. A message sent by a send-receive operation can be
    received by MPI_Recv and a send-receive operation can receive a message sent by an
    MPI_Send.

    MPI_Sendrecv(&data_to_send, send_count, send_type,


    destination_ID, send_tag, &received_data, receive_count,
    receive_type, sender_ID, receive_tag, comm, &status)

    Understanding the Argument Lists:

     data_to_send: variable of a C type that corresponds to the MPI send_type supplied


    below
     send_count: number of data elements to send(int)
     send_type: datatype of elements to send (one of the MPI datatypehandles)

    Raheel Amjad 2018-CPE-07


    Lab # 7 – Parallel & Distributed Computing (CPE-421)

     destination_ID: process ID of the destination(int)


     send_tag: send tag(int)
     received_data: variable of a C type that corresponds to the MPI receive_type
    supplied below
     receive_count: number of data elements to receive(int)
     receive_type: datatype of elements to receive (one of the MPI datatypehandles)
     sender_ID: process ID of the sender(int)
     receive_tag: receive tag(int)
     comm: communicator(handle)
     status: status object(MPI_Status)

    Conclusion:

    Raheel Amjad 2018-CPE-07

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