AI System Hardware/Software Co-Design request for proposals
This Research Award is now closed
Facebook is pleased to invite university faculty to respond to this call for research proposals on AI System Hardware/Software Co-Design.
Co-design implies simultaneous design and optimization of several aspects of the system, including hardware and software, to achieve a set target for a given system metric, such as throughput, latency, power, size or their combination. Deep learning has been particularly amenable to such co-design processes across various parts of the software and hardware stack. This has led to a variety of novel algorithms, numerical optimizations and AI hardware. Facebook AI teams have also been using co-design to develop high-performance AI solutions for both existing as well as future AI hardware, and we are currently looking to further explore co-design opportunities across a number of new dimensions.
Applications are now closed
Due to the number of proposals, we plan to share the results of this research award in early May 2019.
Launch Date January 8, 2019
Winners Announced May 2019
Areas of Interest
Facebook is especially interested in soliciting proposals for the wide range of AI hardware/algorithm co-design research areas, including but not limited to:
- Model compression (with particular focus on recommender systems and large embedding tables)
- Scalable communication-aware distributed training algorithms
- Processing in-memory hardware architectures for efficient and scalable machine learning
- Hardware efficiency-aware neural architecture search
- Graph-based recommender systems with implications on hardware (graph learning). Emphasis on algorithms like Deepwalk and convolutional approaches like GraphSAGE
- End-to-end hardware/software co-design automation for deep learning
- Optimizing mixed-precision linear algebra operations for AI systems
Applicants should submit a proposal detailing what contribution their research is expected to make, how the research domain will benefit from the work, project timeline and a budget overview of how the proposed funding will be used.
Proposals are highly encouraged to focus funding on project personnel, especially PhD students. Proposals from small collaborative teams, particularly with PIs bridging areas of systems and machine learning, are also encouraged. A total of six awards are available, up to to $50,000 each, depending on the specific requirements. Payment will be made to the proposer’s host university as an unrestricted gift.
Proposals should include
- A summary of the project explaining the area of focus, a description of techniques, any relevant prior work and a timeline with milestones and expected outcomes
- Clear and concise statement of the research, project time line and a proposed budget (2-3 pages total)
- Names of the researcher(s) involved in the proposed work and host academic research institution
- Indication of any previous or current connections/collaborations with Facebook (in which case please name the Facebook contacts)
Timing and dates
- Applications are now closed.
- Due to the number of proposals, we plan to share the results of this research award in early May 2019.
Successful awardees will be listed on the Facebook Research website and will be encouraged to openly publish any findings/insights from their work.
Terms & Conditions
- By submitting a proposal, you are authorizing Facebook to evaluate the proposal for a potential award, and you agree to the terms herein.
- You agree that Facebook will not be required to treat any part of the proposal as confidential or protected by copyright.
- You agree and acknowledge that personal data submitted with the proposal, including name, mailing address, phone number, and email address of you and other named researchers in the proposal may be collected, processed, stored and otherwise used by Facebook for the purposes of administering the website and evaluating the contents of the proposal.
- You acknowledge that neither party is obligated to enter into any business transaction as a result of the proposal submission, Facebook is under no obligation to review or consider the proposal, and neither party acquires any intellectual property rights as a result of submitting the proposal.
- Any feedback you provide to Facebook in the proposal regarding its products or services will not be treated as confidential or protected by copyright, and Facebook is free to use such feedback on an unrestricted basis with no compensation to you.
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