What is Chapel?
Chapel is a programming language designed for productive parallel computing at scale.
Why Chapel? Because it simplifies parallel programming through elegant support for:
- distributed arrays that can leverage thousands of nodes' memories and cores
- a global namespace supporting direct access to local or remote variables
- data parallelism to trivially use the cores of a laptop, cluster, or supercomputer
- task parallelism to create concurrency within a node or across the system
- productive: code tends to be similarly readable/writable as Python
- scalable: runs on laptops, clusters, the cloud, and HPC systems
- fast: performance competes with or beats C/C++ & MPI & OpenMP
- portable: compiles and runs in virtually any *nix environment
- open-source: hosted on GitHub, permissively licensed
New to Chapel?
As an introduction to Chapel, you may want to...- watch an overview talk or browse its slides
- read a blog-length or chapter-length introduction to Chapel
- learn about projects powered by Chapel
- check out performance
highlights like these:
- browse sample programs or learn how to write distributed programs like this one:
use CyclicDist; // use the Cyclic distribution library
config const n = 100; // use --n=<val> when executing to override this default
forall i in {1..n} dmapped Cyclic(startIdx=1) do
writeln("Hello from iteration ", i, " of ", n, " running on node ", here.id);
What's Hot?
- Interested in working on Chapel as your job? We're hiring!
- All CHIUW 2020 talks are now available from the program page or YouTube
- Watch Bill Reus' keynote, Arkouda: Interactive
Supercomputing for Data Science
- Chapel 1.22 is now available—download your copy or browse its release notes
- Gmys et al. have a new paper comparing Chapel, Julia, Python/Numba to OpenMP
- Consider submitting work on Chapel to PAW-ATM 2020
or ESPM2 2020
- Also see: What's New?