MODELS AND TRENDS IN PARALLEL PROGRAMMING

Abstract

This paper introduces and discusses programming models for parallel processing and recent trends in the area of parallel programming. The paper discusses different parallel programming languages and tools that reflect various parallel computation models. These language differ in expressiveness, portability and performance. Software design and implementation largely varies by using different languages that make the programmer task easy or complex. We describe here the design goals and the main issues of parallel programming models and languages belonging to the following categories: shared-space based languages, message-based languages, parallel toolkits, data-parallel languages, parallel declarative languages, parallel object-oriented languages, and parallel composition-based languages. Tools and languages such as HPF, Linda, Java, OpenMP, PVM, MPI, Parallel C+ +, Sisal, Orca, Mentat, SkieCL, BSP and others are described in some detail. Their main features for design and implementation of high performance applications are discussed. Finally, we outline directions of research and development in the parallel programming area with a special attention to novel approaches based on high-level programming structures that make transparent to the users the architectural details of parallel computing machines.