## Learn to Use ITensor

main / classes / parallel C++v3 | C++v2

# Support for MPI Parallelism

The messsage passing interface (MPI) is a framework for creating parallel algorithms based around passing data between parallel workers or "nodes". In this paradigm, the nodes do not share memory (in the sense of being able to write to the same memory addresses) but instead send data in the form of "messages".

The file util/parallel.h provides some convenient wrappers and facilities for using MPI to communicate ITensor objects and other data types between nodes.

To use the code in this file, you must have an implementation of MPI (such as Open MPI, LAM, or MPICH) and provide both an include path to the file mpi.h as well as link to the relevant MPI library files. Most MPI implementations provide a command named mpic++ or mpicxx that acts as a replacement C++ compiler that will automatically include MPI support. These commands also typically come with an option that lets you view the correct set of compiler and linker flags for your system. (For some versions of MPI, the command is mpicxx --showme.)

At a lower level, MPI is a set of rather simple C functions. The parallel.h file provided in ITensor mainly provides some useful wrappers around certain functions that are helpful to use together, and it provides a convenient C++ interface. You are encouraged to study the parallel.h code as it is not too complex and is written in a fairly generic way (not specific to ITensor internals).

## Initializing the MPI Environment

The simplest MPI parallel code you can write using the parallel.h tools is as follows

#include "itensor/all.h"
#include "itensor/util/parallel.h"
using namespace itensor;

int
main(int argc, char* argv[])
{
Environment env(argc,argv);

if(env.firstNode()) printfln("There are %d nodes",env.nnodes());

return 0;
}


To run this code, you compile it (either using mpic++ or with the flags suggested by mpic++) then run it using a command similar to:

mpirun --np 4 ./myprogram


The precise command depends on your particular MPI implementation.;

Constructing the Environment object env initializes the MPI environment and is required. This establishes the basic setup of the requested number of nodes (i.e. requested by mpirun)

## Simple Communication

An easy to use and convenient type of communication is the broadcast. This takes a variable whose value is set on the root node (node number 0) and sends it to all of the other nodes. Afterwards the variable will have the same value on every node.

For example, consider the following code:

int i = 0;
if(env.firstNode()) i = 5;

printfln("Node %d has i=%d",env.node(),i);

printfln("Now node %d has i=%d",env.node(),i);


Running it should print something like:

"Node 1 has i=0"
"Node 0 has i=5"
"Now node 0 has i=5"
"Now node 1 has i=5"


I say "something like" because due to the vagaries of parallel execution, these lines could be printed in a different order and the text can even sometimes be garbled if different nodes print on top of each other.

## Communicating to a Specific Node

For sending data from one node to just one other node, parallel.h provides a class called MailBox. The MailBox class is mainly a wrapper around MPI_Send, which does a blocking send, but the MailBox class does other helpful things too such as breaking data into smaller pieces to avoid exceeding MPI buffer sizes for large sends.

To set up a MailBox object, just provide the Environment object and the number (0 indexed) of the other node the MailBox should always send to.

For node 0 to set up a MailBox it can use to send data to node 1, it can do:

//On node 0
auto mbox = MailBox(env,1);


Then to send an object to node 1:

mbox.send(obj);


Any object can be sent as long as it is plain data or it supports the .read(std::istream&) and .write(std::ostream&) const methods, which define how to convert the object from and to binary streams.

After the sending node begins a send, it waits for the receiving node to call receive, like this:

//On node 1
auto mbox = MailBox(env,0);
...