The following funding opportunity was shared by Lewis-Burke Associates LLC on April 19, 2022.
The Department of Energy (DOE) Advanced Scientific Computing Research (ASCR) program recently released five funding opportunities that would provide about $100 million to support mathematics and computer science research. In general, ASCR supports specialized computer science and mathematics research and development aimed at solving high-performance computing challenges and developing next-generation computing technologies. ASCR, with congressional support through annual appropriations, continues to grow funding for math and computer science research, especially at research universities, consistent with recommendations from its advisory committee. Over the last five years, ASCR invested heavily in the development and procurement of exascale computing systems, but is now transitioning to research and development of next-generation computing systems and diverse architectures and growing workforce development programs. Below is a list of the most recent funding solicitations followed by a more detailed analysis of each opportunity.
- ASCR will fund five-year, multi-institutional collaborations for projects that focus on the challenge of integrating multiple mathematical techniques to obtain solutions.
- Pre-applications are due May 27, 2022. Institutions are limited to 2 proposals as the lead.
- Award size is expected to be $2 million - $3 million per year.
- ASCR will fund two-year, multi-institutional collaborations for projects to explore innovative approaches in priority research areas such as artificial intelligence, quantum information science, high-productivity programming, and discrete event simulation.
- Pre-applications are due May 20, 2022. Institutions are limited to 6 proposals as the lead.
- Award size for non-National Lab led proposals is $200,000 per year.
- ASCR will fund up individual or multi-institution teams for up to three years to optimize the management of massive amounts of data that must be moved and reproducibly analyzed using sophisticated mathematical techniques, including machine learning.
- Pre-applications are due May 5, 2022. Institutions are limited to 2 proposals as the lead.
- Award size for non-National Lab led proposals is $100,000 - $300,000 per year.
- ASCR will fund individual or multi-institution teams to aid in the development of informative and interactive visualization of complex scientific data.
- Pre-applications are due May 10, 2022. Institutions are limited to 2 proposals as the lead.
- Award size for non-National Lab led proposals is $100,000 - $300,000 per year.
- ASCR will fund individual or multi-institution teams to develop randomized algorithms for discrete and combinatorial problems in DOE’s mission areas.
- Pre-applications are due May 19, 2022. Institutions are limited to 2 proposals as the lead.
- Award size is $400,000 - $800,000 per year.
Mathematical Multifaceted Integrated Capability Centers (MMICCs)
ASCR released a $40 million funding opportunity for new Mathematical Multifaceted Integrated Capability Centers (MMICCs). The centers will support large teams of mathematicians working across mathematics disciplines on complex, multiscale research challenges. The research should focus on mathematical abstractions of science problems in key DOE challenge areas, such as the smart grid or materials for energy applications. This will allow teams to collaborate in innovative ways to address grand challenge problems more effectively than focusing on a single issue.
This is the third time the MMICCs program has been competed. The previous round of projects included a focus on the mathematics of rare events as applied to the power grid; the integration of physical governing equations and neural networks to increase the efficiency and accuracy of scientific machine learning; and methods for making optimization and inversion under uncertainty tractable for additive manufacturing and advanced materials.
Due Dates: Pre-applications are required and due on May 17, 2022. Full applications are due on June 28, 2022.
Total Funding and Award Size: The centers will be funded for five-year terms. DOE anticipates awarding three to four centers with an award size of $2 million to $3 million per year. Cost sharing is not required.
Sources and Additional Background: The complete DOE solicitation is available online.
Exploratory Research for Extreme-Scale Science (EXPRESS)
ASCR released a $20 million funding opportunity for new projects in basic research to explore potentially high impact approaches in extreme-scale science and scientific computing. Extreme-scale science is focused on utilizing game changing technology development in scientific computing and developing effective paradigms and approaches to utilize the new technology most efficiently. 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. Specific topic areas of interest include:
- Federated Scientific Machine Learning
- Differentiable Programming
- Explainable Artificial Intelligence
- Parallel Discrete Event Simulation
- Quantum Algorithms and Mathematical Methods
- Quantum Computing at the Edge
Due Dates: Pre-applications are required and due on May 12, 2022. Full applications are due on June 23, 2022.
Total Funding and Award Size: The centers will be funded for two-year terms. DOE anticipates awarding 25-35 awards with a size of $200,000 for a non-National Lab or $450,00 for a National Lab. Cost sharing is not required.
Sources and Additional Background: The complete DOE solicitation is available online.
Management and Storage of Scientific Data
ASCR released a $13 million funding opportunity for research to optimize the management of massive amounts of data that must be moved and reproducibly analyzed using sophisticated mathematical techniques, including machine learning. Proposals should focus on developing new capabilities to utilize smart storage and networking hardware that may provide transformational breakthroughs to challenges that science faces when using large amounts of data. Research breakthroughs would benefit a wide range of DOE activities including materials science, chemistry, climate modelling, the development of new clean energy sources, and new approaches to increasing energy efficiency and reducing energy consumption. Topics of interest include Priority Research Directions identified in the ASCR Workshop on the Management and Storage of Scientific Data, held in January 2022:
- High-productivity interfaces for accessing scientific data efficiently;
- Understanding the behavior of complex data management systems in DOE science
- Rich metadata and provenance collection, management, search, and access; and
- Reinventing data services for new applications, devices, and architectures.
Due Dates: Pre-applications are required and due on May 5, 2022. Full applications are due on June 13, 2022.
Total Funding and Award Size: The projects will be funded for three years. Award size for non-National Lab awards is $100,000 - $300,000 and for National Lab awards is $250,000 - $750,000.
Sources and Additional Background: The complete DOE solicitation is available online.
Data Visualization for Scientific Discovery, Decision-Making, and Communication
ASCR released a $13 million funding opportunity for research in new techniques and theory needed to aid in the development of informative and interactive visualization of complex scientific data of interest to DOE priorities, including visualizing Earth systems, astrophysical systems, advanced manufacturing, and quantum systems. Projects are expected to help engage a broader range of scientific users through more user-friendly simulations and visualizations of complex data. Topics of interest are derived from Priority Research Directions highlighted in the ASCR Workshop on the Visualization for Scientific Discovery, Decision-making, and Communication, held in January 2022 and proposals must address one of the following topics:
- Advancing theory and techniques for visualization to support the analysis and understanding of complex scientific data;
- Introducing interoperable and adaptable visualization to support diverse scientific workflows across all scales; and/or
- Harnessing technology innovations to accelerate science through visualization.
Due Dates: Pre-applications are required and due on May 10, 2022. Full applications are due on June 21, 2022.
Total Funding and Award Size: The projects will be funded for three-year. Award size for non-National Lab awards is $100,000 - $300,000 and for National Lab awards is $250,000 - $750,000.
Sources and Additional Background: The complete DOE solicitation is available online.
Randomized Algorithms for Combinational Scientific Computing
ASCR released a $10 million funding opportunity to enable researchers to investigate the novel use of randomness in internal algorithmic decisions for accelerating the time to solution, increasing the size of problems that can be solved, or improving the reliability of predictions. Proposals should advance DOE priority areas such as climate science, astrophysics, fusion, materials design, and the Energy Earthshots initiative.
The solicitation builds off of the Priority Research Directions highlighted in the ASCR Workshop on Randomized Algorithms for Scientific Grouping, held in January 2021, and the subsequent Workshop Report. Key research areas include:
- Randomized algorithms for discrete problems that cannot be modelled as networks
- Randomized algorithms for solving well-defined problems on networks
- Universal sketching and sampling on discrete data
- Randomized algorithms for combinatorial and discrete optimization
- Randomized algorithms for machine learning on networks
Due Dates: Pre-applications are required and due on May 19, 2022. Full applications are due on June 30, 2022.
Total Funding and Award Size: Projects will be funded for three years. DOE plans on awarding 4- 9 awards. Award size is $400,000 - $800,000 a year.
Sources and Additional Background: The complete DOE solicitation is available online.
— Lewis-Burke Associates LLC