SBIR/STTR Research Award
Resistive Deep Learning Neuromorphic Processors
Award amount
$124,795Program and phase
SBIR · Phase IAward year
2020Award details
- Awarding agency
- National Aeronautics and Space Administration
- Branch
- Not reported
- Recipient company
- BRISK COMPUTING LLC
- Proposal award date
- 2020-08-24
- Contract end date
- 2021-03-01
- UEI
- EH2QT9SLFT43
- Solicitation number
- SBIR_20_P1
- Topic code
- H6
Research abstract
Artificial intelligence (AI) algorithms have many applications in satellites and are generally quite compute intensive. The objective of this work is to develop highly Size, Weight, and Power (SWaP) efficient neuromorphic processors that can run AI algorithms. We will develop resistive crossbar neuromorphic processors, with the primary target being deep learning algorithms. We plan to process various types of signals very efficiently ndash; these include sensor and cognitive communication applications. The key outcomes of the work will be the processor design, processor performance metrics on various applications, and software for the processor.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
- Adaptive Neuromorphic Processors for Cognitive Communications
- Adaptive Neuromorphic Processors for Cognitive Communications
- Resistive Deep Learning Neuromorphic Processors
- Rapid Design Space Exploration for Mapping Applications to Neuromorphic Processors
- Spiking Neuromorphic Software Defined Networking
Research funding history
6 SBIR/STTR records share this UEI (2020–2023). Reported award amounts total $2,189,763. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: National Aeronautics and Space Administration, Department of Defense