Opportunity Information: Apply for DE FOA 0002352
The Department of Energy (DOE) Office of Science, through its Advanced Scientific Computing Research (ASCR) program, issued this grant opportunity to fund basic research that pushes neuromorphic computing forward as a practical, brain-inspired approach for accelerating scientific discovery. The core idea behind the call is that future breakthroughs in DOE-relevant science will increasingly depend on how well researchers can create, move, and analyze massive, complex datasets coming from extreme-scale simulations, experiments, and observational facilities, especially in the post-exascale era. DOE is explicitly looking for high-risk, high-reward work that does more than incremental improvements and instead explores fundamentally new ways neuromorphic systems could help meet emerging computational demands.
A central motivation is energy efficiency. The opportunity highlights a growing tension in high performance computing: modern supercomputers can consume power on the order of megawatts, and while heterogeneous architectures have helped keep energy use from rising even faster, energy remains a major limiting factor. In contrast, the human brain operates on the order of watts, illustrating an enormous gap in energy efficiency. Neuromorphic computing is positioned in this announcement as a promising path to narrow that gap by borrowing principles from neuroscience (such as event-driven computation and massively parallel, distributed processing) to perform certain classes of computation with dramatically lower power consumption. The program is therefore aimed at exploring how neuromorphic approaches might provide more energy-efficient computing options for scientific workloads that are becoming increasingly data-intensive and complex.
The announcement also frames neuromorphic computing as a potential response to a broad set of bottlenecks facing scientific computing beyond raw speed. It calls out challenges including high energy usage, memory constraints, concurrency and parallelism limits, heterogeneity, and difficulties with input/output, storage, retrieval, and fault tolerance. In practical terms, this signals interest in research that can show how neuromorphic hardware and algorithms might handle aspects of scientific workflows that are difficult or costly on conventional architectures, particularly where moving and storing data dominates time and energy. The emphasis is not simply on building neuromorphic devices, but on advancing the basic research foundations needed to make neuromorphic computing a useful scientific tool in realistic computing environments.
In terms of the funding details provided, the opportunity is a discretionary grant from the DOE Office of Science (CFDA 81.049) under Funding Opportunity Number DE FOA 0002352. Eligibility is listed as unrestricted, meaning proposals could come from a wide range of entity types, subject to any additional eligibility clarifications in the full announcement text. The award ceiling is stated as $400,000, with an expectation of about 7 awards. The FOA was created on April 30, 2020, and the original closing date was July 1, 2020. Overall, the call is best understood as an attempt by DOE to seed foundational research that could make neuromorphic computing a credible, energy-efficient complement to traditional high performance computing for future scientific discovery.Apply for DE FOA 0002352
- The Department of Energy - Office of Science, Office of Science in the science and technology and other research and development sector is offering a public funding opportunity titled "Neuromorphic Computing for Accelerating Scientific Discovery" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 81.049.
- This funding opportunity was created on Apr 30, 2020.
- Applicants must submit their applications by Jul 01, 2020. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $400,000.00 in funding.
- The number of recipients for this funding is limited to 7 candidate(s).
- Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.
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Frequently Asked Questions (FAQs)
What agency and program are offering this grant opportunity?
This opportunity is offered by the U.S. Department of Energy (DOE) Office of Science through its Advanced Scientific Computing Research (ASCR) program.
What is the main purpose of this funding opportunity?
The purpose is to support basic research that pushes neuromorphic computing forward as a practical, brain-inspired approach for accelerating scientific discovery, especially for DOE-relevant science.
What does DOE mean by neuromorphic computing in this context?
In this call, neuromorphic computing is framed as a brain-inspired computing approach that borrows principles from neuroscience, such as event-driven computation and massively parallel, distributed processing, with the aim of performing certain computations much more energy-efficiently than conventional systems.
Why is DOE interested in neuromorphic computing now?
DOE emphasizes that future scientific breakthroughs will increasingly depend on the ability to create, move, and analyze massive, complex datasets produced by extreme-scale simulations, experiments, and observational facilities, particularly in the post-exascale era. Neuromorphic computing is positioned as a potential way to meet these emerging computational demands.
What kinds of scientific computing challenges is this FOA trying to address?
The announcement highlights multiple bottlenecks beyond raw speed, including high energy usage, memory constraints, limits in concurrency and parallelism, heterogeneity challenges, and difficulties related to input/output (I/O), storage, retrieval, and fault tolerance.
How important is energy efficiency to this opportunity?
Energy efficiency is presented as a central motivation. The FOA notes that modern supercomputers can consume power on the order of megawatts, while the human brain operates on the order of watts, underscoring a major energy-efficiency gap that neuromorphic approaches might help narrow.
Is DOE looking for incremental improvements or more exploratory research?
DOE explicitly states interest in high-risk, high-reward research that goes beyond incremental improvements and instead explores fundamentally new ways neuromorphic systems could help address emerging computational demands for scientific discovery.
Is this opportunity focused on building neuromorphic devices?
The FOA indicates the emphasis is not simply on building neuromorphic devices. It is focused on advancing the basic research foundations needed to make neuromorphic computing a useful scientific tool in realistic computing environments.
What kinds of workloads or environments are relevant to this FOA?
The call is motivated by scientific workloads associated with extreme-scale simulations, experiments, and observational facilities, where datasets are massive and complex and where moving and storing data can dominate time and energy costs.
What is the Funding Opportunity Number (FOA number)?
The Funding Opportunity Number is DE FOA 0002352.
What is the CFDA number listed for this grant?
The opportunity is listed under CFDA 81.049.
What type of funding mechanism is this?
This is a discretionary grant issued by the DOE Office of Science.
Who is eligible to apply?
Eligibility is listed as unrestricted, meaning proposals could come from a wide range of entity types, subject to any additional eligibility clarifications that may be included in the full announcement text.
What is the maximum award amount (award ceiling)?
The award ceiling is stated as $400,000.
How many awards does DOE expect to make?
The opportunity indicates an expectation of about 7 awards.
When was this FOA created?
The FOA was created on April 30, 2020.
What was the original closing date?
The original closing date was July 1, 2020.
What is meant by "post-exascale era" in the FOA description?
In the context provided, "post-exascale era" refers to the period after exascale computing becomes available, where scientific computing demands continue to grow and challenges increasingly center on managing and analyzing extremely large, complex datasets rather than only increasing peak computational speed.
How does the FOA describe the relationship between neuromorphic computing and traditional HPC?
The call frames neuromorphic computing as a potentially credible, energy-efficient complement to traditional high performance computing (HPC), particularly for future scientific discovery needs that are data-intensive and complex.
What problem areas related to data movement does DOE highlight?
DOE notes practical challenges where moving and storing data can dominate both time and energy, and signals interest in research showing how neuromorphic hardware and algorithms might handle parts of scientific workflows that are difficult or costly on conventional architectures.
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