a Productive Parallel Programming Language

Technologies
c, python, c++, chapel, high performance computing
Topics
compilers, programming languages, distributed computing, high performance computing, parallel computing
a Productive Parallel Programming Language

Chapel is an open-source programming language designed for productive parallel computing at scale. Chapel is implemented with portability in mind, permitting Chapel to run on multicore desktops and laptops, commodity clusters, and the cloud, in addition to the high-end supercomputers for which it was designed. Chapel's design and development are being led by Cray Inc. in collaboration with academia, computing centers, and industry. Chapel offers a unique experience for students to work on projects involving high-performance computing, parallel programming, and compiler development.

Core features

Native Parallelism

Chapel supports parallelism at the language level. For instance, Chapel provides a "coforall" loop, which is similar to a "for" loop and creates a separate task per iteration of the loop body. These explicit parallelism features make it easier to reason about the parallelism in your algorithm and program.

Data and Task Locality

When working on a large machine, the location of some data relative to the task which uses it or other data with which it must work plays a key role in performance. Chapel provides features which allow you to control that placement, both within a data structure and outside it.

Multiresolution Philosophy

Chapel is designed around a multiresolution philosophy, permitting users to initially write very abstract code and then incrementally add more detail until they are as close to the machine as their needs require.

Modern Language Features

Chapel supports code reuse and rapid prototyping via object-oriented design, type inference, and features for generic programming.

Interoperability

Existing code from other languages can be integrated into Chapel programs (or vice-versa) via interoperability features.

2019 Program

Successful Projects

Contributor
Mohammed Nafees
Mentor
Michael Ferguson, goovie
Organization
Chapel
Improvements to Chapel LLVM Backend
The Chapel compiler optionally can produce LLVM IR and use LLVM optimizations with –llvm. Going forward, Chapel will use LLVM more and more because...
Contributor
Alvis Wong
Mentor
Engin Kayraklioglu
Organization
Chapel
Distributed Sparse Linear Algebra Library in Chapel
This project includes adding BLAS, Sparse linear algebra and iterative solvers into Chapel.
Contributor
Garvit Dewan
Mentor
LouisJenkinsCS
Organization
Chapel
Concurrent-Safe Memory Reclamation Systems
Currently Chapel has support for ‘shared’ lifetime-managed objects, which is implemented using reference-counting. Unfortunately reference counting...
Contributor
Krishna Kumar Dey
Mentor
Lydia D., Ben Albrecht
Organization
Chapel
Unit Test Framework
Deployment is the last stage in the application development process and before that, any application undergoes a comprehensive testing process to...