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.

lightbulb_outline View ideas list

Technologies

  • chapel
  • python
  • high performance computing
  • c
  • c++

Topics

comment IRC Channel
email Mailing list
mail_outline Contact email

Chapel 2019 Projects

  • Garvit Dewan
    Concurrent-Safe Memory Reclamation Systems
    Currently Chapel has support for ‘shared’ lifetime-managed objects, which is implemented using reference-counting. Unfortunately reference counting...
  • Alvis Wong
    Distributed Sparse Linear Algebra Library in Chapel
    This project includes adding BLAS, Sparse linear algebra and iterative solvers into Chapel.
  • Mohammed Nafees
    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...
  • Krishna Kumar Dey
    Unit Test Framework
    Deployment is the last stage in the application development process and before that, any application undergoes a comprehensive testing process to...
close

2019