Affiliations: Institute for Software Technology and Parallel Systems, University of Vienna, Liechtensteinstrasse 22, A‐1090, Vienna, Austria; e‐mail: {barbara,zima}@par.univie.ac.at | Computer Science Department, University of Wyoming, Laramie, WY 82071‐3682, USA; e‐mail: [email protected] | Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, Mail Stop 403, Hampton, VA 23681‐0001, USA; e‐mail: {pm,jvr}@icase.edu
Abstract: Data parallel languages, such as High Performance Fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not fit well into the data parallel paradigm. In this paper we present Opus, a language designed to fill this gap. The central concept of Opus is a mechanism called ShareD Abstractions (SDA). An SDA can be used as a computation server, i.e., a locus of computational activity, or as a data repository for sharing data between asynchronous tasks. SDAs can be internally data parallel, providing support for the integration of data and task parallelism as well as nested task parallelism. They can thus be used to express multidisciplinary applications in a natural and efficient way. In this paper we describe the features of the language through a series of examples and give an overview of the runtime support required to implement these concepts in parallel and distributed environments.
