SUMMARY
The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic research to explore potentially high-impact approaches in scientific computing and extreme-scale science.
SUPPLEMENTARY INFORMATION
Extreme-scale science recognizes that disruptive technology changes are occurring across science applications, algorithms, computer architectures and ecosystems. Recent reports point to emerging trends and advances in high-end computing, massive datasets, scientific machine learning, artificial intelligence (AI) on increasingly heterogeneous architectures, including neuromorphic and quantum systems. Significant innovation will be required in the development of effective paradigms and approaches for realizing the full potential of scientific computing from emerging technologies. Proposed research should not focus strictly on a specific science use case, but rather on creating the body of knowledge and understanding that will inform future advances in extreme-scale science. Consequently, the funding from this FOA is not intended to incrementally extend current research in the area of the proposed project. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches.
RESEARCH OPPORTUNITIES
Exploratory Research for Scientific Computing (EXPRESS) opportunities exist for the following research topics (See FOA for full details):
- Federated Scientific Machine Learning
- Differentiable Programming
- Explainable Artificial Intelligence
- Parallel Discrete Event Simulation
- Quantum Algorithms and Mathematical Methods
- Quantum Computing at the Edge
Applications submitted in response to this FOA must substantially address one of these six research topics. Additional details about each topic are included in the full FOA.
If you intend to submit complete the notification form to provide your contact information and the title and brief description of your project.
Questions concerning the limited submissions process may be submitted to limitedsubs@psu.edu.