DOE EXPRESS 2022 Exploratory Research for Extreme Scale Science: Harvard Pre-Proposal Deadline
Date and Time
DOE EXPRESS 2022 Exploratory Research for Extreme Scale Science
Harvard Pre-Proposal Deadline: April 27, 2022
FAS/SEAS/OSP Pre-Application Deadline: May 9, 2022
Sponsor Pre-Application Deadline: May 12, 2022
FAS/SEAS/OSP Full Proposal Deadline: June 14, 2022
Sponsor Full Proposal Deadline: June 23, 2022
Award Amount: $200,000/year for two years
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. 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.
Exploratory Research for Scientific Computing (EXPRESS) opportunities exist for the following research topics:
- Federated Scientific Machine Learning
- Differentiable Programming
- Explainable Artificial Intelligence
- Parallel Discrete Event Simulation
- Quantum Algorithms and Mathematical Methods
- Quantum Computing at the Edge