Chapel (language)
Chapel is a parallel programming language developed for high-performance computing that provides high-level, productivity-oriented abstractions for both data parallelism and task parallelism across multicore, cluster, and…
Definition
Chapel is a parallel programming language developed for high-performance computing that provides high-level, productivity-oriented abstractions for both data parallelism and task parallelism across multicore, cluster, and supercomputer-scale systems.
Overview
Chapel was developed by Cray Inc. (later part of Hewlett Packard Enterprise) starting in 2004 as part of DARPA's High Productivity Computing Systems (HPCS) program, which challenged vendors to design languages and systems that would make supercomputer-scale programming dramatically more productive without sacrificing performance. Traditional high-performance computing at the time (and largely still today) relies on combining a base language like C or Fortran with separate libraries such as MPI for distributed communication and OpenMP for shared-memory parallelism — an approach that works but forces programmers to reason about parallelism and data distribution using low-level, loosely integrated tools. Chapel's goal was to express both parallelism and data distribution as first-class language features instead. Chapel introduces the concept of 'locales' — an abstraction representing a unit of the target machine with its own processors and memory, such as a compute node in a cluster — and 'domains,' which describe index sets (potentially multi-dimensional and distributed across locales) over which arrays and parallel operations are defined. This lets a programmer write a single, relatively high-level loop or array expression and let the language runtime handle distributing that work and data across many locales, rather than manually orchestrating message passing. Chapel supports both data parallelism (operating uniformly over the elements of a domain or array) and task parallelism (explicit `begin`, `cobegin`, and `coforall` constructs for spawning concurrent tasks), giving programmers a unified toolkit for the different patterns common in scientific and numerical computing. Chapel compiles to efficient native code and is designed to scale from a single laptop up to systems with hundreds of thousands of cores, aiming to close the gap between the productivity of high-level languages like Python and the performance of Fortran/C/MPI. It has an active open-source community and continues to be used and developed primarily within the HPC and scientific computing research communities, rather than in general-purpose application development.
Key Features
- First-class language support for both data parallelism and task parallelism
- 'Locales' abstraction representing distributed compute-and-memory units of a target machine
- 'Domains' describing (potentially multi-dimensional, distributed) index sets for arrays and loops
- High-level syntax intended to replace low-level combinations of C/Fortran with MPI and OpenMP
- Explicit task-parallel constructs (begin, cobegin, coforall) alongside data-parallel array operations
- Designed to scale from a laptop to supercomputer-class clusters with the same source code
- Open-source, with development historically led by Cray/HPE and an academic HPC community