Computer Science

The ASCR Computer Science research program supports long-term, basic research that enables computing and networking at extreme scales and the understanding of extreme scale and complex data from both simulations and experiments. It aims to make high-performance scientific computers and networks highly productive and efficient to solve scientific challenges, while attempting to reduce domain science application complexity as much as possible. The computer science program does this in the context of sharp increases in the heterogeneity and complexity of computing systems; the need to integrate simulation, data analysis, and other tasks seamlessly and intelligently into coherent and usable workflows; and the challenges posed by highly novel computing platforms, such as neuromorphic and quantum systems.

Key activities include support for foundational research in:

  • Developing adaptive, portable, high-performance scientific software, including testing, validation, and verification
  • Programming technologies and tools for, and co-design of, state-of-the-art and future computing systems, including quantum-computing systems
  • Distributed systems, including quantum networks, and workflow development integrating simulation, experimental control, data analysis, and data visualization
  • Techniques for integrating and scaling scientific AI along with making research data and AI models findable, accessible, interoperable, and reusable (FAIR)

These activities provide the foundation for increasing the capability of the national scientific computing and data ecosystem by focusing on long-term research to develop software, algorithms, and methods that anticipate future hardware challenges and opportunities as well as science application needs.

ASCR Funding

Award abstracts and information about awards made prior to FY2018 can be found here.

ASCR Workshops and Reports

Workshop and reports completed prior to FY2018 can be found here.

ASCR Meetings

Other Notable Reports

Computer Science Program Managers:

Hal Finkel
Computer Science

Marco Fornari
Quantum Computing

Margaret Lentz
Data and Visualization

Kalyan Perumalla
Systems and Network Research