Chapel (programming language)
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|
| Paradigm |
Object-oriented Partitioned global address space Parallel programming |
|---|---|
| Designed by | David Callahan, Hans Zima, Brad Chamberlain, John Plevyak |
| Developer | Cray Inc. |
| First appeared | 2009 |
| Stable release |
1.13.1 / June 14, 2016
|
| Typing discipline |
static inferred |
| Platform | multiplatform |
| OS | Mac OS, Linux, POSIX, Windows (with Cygwin) |
| License | Apache 2 |
| Filename extensions | .chpl |
| Website | chapel |
| Influenced by | |
| Ada, C, Fortran, C++, Java, C#, HPF, ZPL, Cray MTA / XMT extensions to C and Fortran. | |
Chapel, the Cascade High Productivity Language, is a parallel programming language developed by Cray. It is being developed as part of the Cray Cascade project, a participant in DARPA's High Productivity Computing Systems (HPCS) program, which had the goal of increasing supercomputer productivity by the year 2010. It is being developed as an open source project, under version 2 of the Apache license.
Chapel aims to improve the programmability of parallel computers in general and the Cascade system in particular, by providing a higher level of expression than current programming languages do and by improving the separation between algorithmic expression and data structure implementation details.
The language designers aspire for Chapel to bridge the gap between current HPC programming practitioners, who they describe as Fortran, C or C++ users writing procedural code using technologies like OpenMP and MPI on one side, and newly graduating computer programmers who tend to prefer Java, Python or Matlab with only some of them having experience with C++ or C. Chapel should offer the productivity advances offered by the latter suite of languages while not alienating the users of the first.
Chapel supports a multithreaded parallel programming model at a high level by supporting abstractions for data parallelism, task parallelism, and nested parallelism. It enables optimizations for the locality of data and computation in the program via abstractions for data distribution and data-driven placement of subcomputations. It allows for code reuse and generality through object-oriented concepts and generic programming features. For instance, Chapel allows for the declaration of locales.
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