Distributed-memory data-parallel hello, world¶

View hello4-datapar-dist.chpl on GitHub

This program uses Chapel’s distributed data parallel features to create a parallel hello world program that utilizes multiple cores on multiple locales (compute nodes). The number of locales on which to run is specified on the executable’s command line using the -nl or –numLocales flag (e.g., ./hello -nl 64). This test is very similar to hello-datapar.chpl, so we won’t repeat the explanation of concepts introduced there.

To start, we’ll ‘use’ the standard Cyclic distribution module (CyclicDist) to access a domain map that supports the round-robin distribution of indices to locales.

use CyclicDist;


Declare the number of messages to print:

config const numMessages = 100;


Here, we declare a domain (an index set) named MessageSpace that represents the indices 1..numMessages and is domain mapped (dmapped) using the standard Cyclic distribution. This causes its indices to be distributed across the locales in a round-robin fashion where startIdx is mapped to locale #0.

const MessageSpace = {1..numMessages} dmapped Cyclic(startIdx=1);


By using the distributed domain MessageSpace to drive the following forall-loop, each iteration will be executed by the locale which owns that index, resulting in the distribution of the work across all the program’s compute nodes. In addition, each locale will also use its available processing units (cores) to execute its local iterations in parallel.

forall msg in MessageSpace do
writeln("Hello, world! (from iteration ", msg, " of ", numMessages,
" owned by locale ", here.id, " of ", numLocales, ")");


Note that by changing the domain map of MessageSpace above (either by changing the arguments to Cyclic or switching to another domain map altogether), we can alter the distribution and scheduling of the forall-loop’s iterations without changing the loop itself.

For further examples of using distributions, refer to examples/primers/distributions.chpl in the Chapel Primers.