The IDEAS project addresses productivity and sustainability concerns that are emerging from important trends in extreme-scale computing for science and engineering.
|IDEAS Software Productivity Project
|Advancing Scientific Productivity through Better Scientific Software: Developer Productivity and Software Sustainability Report
|Developer productivity and software sustainability for extreme-scale CSE
Advances in next-generation computational science and engineering (CSE) require the development of applications that can fully exploit emerging extreme-scale architectures for optimal performance and provide high-fidelity multiphysics and multiscale capabilities. To help address overwhelming complexity, the IDEAS project focuses on improving scientific productivity by qualitatively improving developer productivity (positively impacting product quality, development time, and staffing resources) and software sustainability (reducing the cost of maintaining, sustaining, and evolving software capabilities in the future)—thereby enabling a fundamentally different attitude to creating and supporting CSE applications.
The IDEAS project is partnering with the community to create an extreme-scale scientific software development ecosystem composed of high-quality, reusable CSE software components and libraries; a collection of best practices, processes, and tools; and substantial outreach mechanisms for promoting and disseminating productivity improvements. A goal is to improve CSE productivity by enabling better, faster and cheaper CSE application capabilities for extreme-scale computing.
The report Advancing Scientific Productivity through Better Scientific Software: Developer Productivity and Software Sustainability, released in January 2020 introduces work by the IDEAS-ECP project, part of the DOE Exascale Computing Project (ECP), to foster and advance software productivity and sustainability for extreme-scale CSE, as a key aspect of improving overall scientific productivity. The report explains the IDEAS approach, outcomes, and impact of work (in partnership with the ECP and broader computational science community).
Target readers are all those who care about the quality and integrity of scientific discoveries based on simulation and analysis. While the difficulties of extreme-scale computing intensify software challenges, issues are relevant across all computing scales, given universal increases in complexity and the need to ensure the trustworthiness of computational results.
Sponsored by the U. S. Dept. of Energy