SBIR/STTR Research Award

Resistive Deep Learning Neuromorphic Processors

Award identifier f3940180373ed5f1e8a617a3ee3d5973fdddb662f16bf9c2dfdb6ffcbaed5dc0Awarding agency National Aeronautics and Space Administration

Award amount

$749,997

Program and phase

SBIR · Phase II

Award year

2021

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
BRISK COMPUTING LLC
Proposal award date
2021-09-24
Contract end date
2023-09-23
UEI
EH2QT9SLFT43
Solicitation number
SBIR_20_P2
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.

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

Agency intelligence

National Aeronautics and Space Administration

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