Braid: Integrating Task and Data Parallelism

Report
Authors:West, Emily, Department of Computer ScienceUniversity of Virginia Grimshaw, Andrew, Department of Computer ScienceUniversity of Virginia
Abstract:

Archetype data parallel or task parallel applications are well served by contemporary languages. However, for applications containing a balance of task and data parallelism the choice of language is less clear. While there are languages that enable both forms of parallelism, e.g., one can write data parallel programs using a task parallel language, there are few languages which support both. We present a set of data parallel extensions to the Mentat Programming Language (MPL) which allow us to integrate task parallelism, data parallelism, and nested task and data parallelism within a single language on top of a single run-time system. The result is an object-oriented language, Braid, that supports both task and data parallelism on MIMD machines. In addition, the data parallel extensions define a language in and of itself which makes a number of contributions to the data parallel programming style. These include subset-level operations (a more general notion of element-level operations), compiler provided iteration within a data parallel data set, and the ability to define complex data parallel operations.

Rights:
All rights reserved (no additional license for public reuse)
Language:
English
Source Citation:

West, Emily, and Andrew Grimshaw. "Braid: Integrating Task and Data Parallelism." University of Virginia Dept. of Computer Science Tech Report (1994).

Publisher:
University of Virginia, Department of Computer Science
Published Date:
1994