Simplifying Parallel Programming for CSE Applications using a Multi-Paradigm Approach

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

Scientific applications can model interactions of medicines with proteins, predict the behavior of nano-materials, model the climate, and lead to better understanding of physical phenomenon. These applications demand ever greater computational resources, which can only be supplied by new parallel computers with ever increasing capability and complexity. Parallel computing can bring about new breakthroughs only if the complexity of efficient parallel programming can be overcome. Yet developing parallel applications remains significantly more difficult than serial development. Petascale machines with hundreds of thousands(and possibly millions) of processors add to the complexity, as do new sophisticated algorithms and multi-physics applications. This project is developing a new approach to parallel programming which builds upon the automatic resource management and composibility of the Charm++ framework. This approach includes development of multiple, individually incomplete, programming models. Each model simplifies parallel programming while still covering significant categories of applications. This collection of interoperable models, supported by complete models including Adaptive MPI and Charm++, provides a powerful environment for developing future petascale applications. A compiler framework is being developed which provides a common representation and facilitates compatibility between models. In addition, the vision includes abstractions supported by libraries for commonly needed data types and functionalities. These abstractions will support and interoperate with domain specific frameworks. The results of this project will enable the large community of computational scientists and engineers to harness petascale machines with relative ease in order to generate breakthroughs in scientific discovery and engineering design.