NSF: SHF: PAW: Novel Functionality in Programming Models to Productively Abstract Wavefront Parallel Pattern

PI: Sunita Chandrasekaran
Students: Fabian Mora

Funding Agency: National Science Foundation (NSF)

Duration: 10/01/2018 – 09/30/2023

Project Summary:
The aim of this research project is to design novel high-level programming abstractions for complex parallel patterns in scientific applications as these patterns often require for the programmer to restructure the code thus spending hours to create a new codebase which can be both time-consuming and error-prone. To achieve this, we address the performance and portability questions at the algorithmic-level, programming framework-level and at the software design level. The studies are also suggestive of shortcomings in current programming models paving the way to developing novel insights towards high-level software abstractions for multi-use in different/diverse projects simultaneously.

GitHub: The software is open source and available on GitHub: https://github.com/UD-CRPL/minisweep.

Publications:

Posters and Talks:

  • Robert Searles, Sunita Chandrasekaran, “Abstractions and Directives for Adapting Wavefront Algorithms to Future Architectures”, GTC 2019

  • Robert Searles. Creating Language Extensions For Complex Parallel Patterns, Talk given at National Center for Atmospheric Research (NCAR), 2018, CO

PhD Thesis: