SBIR-STTR Award

DNN Radiation Hardened Co-processor companion chip to NASA's upcoming High-Performance Spaceflight Computing processor
Award last edited on: 3/25/2023

Sponsored Program
SBIR
Awarding Agency
NASA : ARC
Total Award Amount
$123,957
Award Phase
1
Solicitation Topic Code
H6.22
Principal Investigator
Nilesh Gharia

Company Information

Numem Inc (AKA: NVMEngines Inc)

440 North Wolfe Road
Sunnyvale, CA 94085
   (408) 836-8795
   sales@numem.com
   www.numem.com
Location: Single
Congr. District: 17
County: Santa Clara

Phase I

Contract Number: 80NSSC20C0366
Start Date: 8/28/2020    Completed: 3/1/2021
Phase I year
2020
Phase I Amount
$123,957
New Space Directive has opened up new challenges and opportunities in AI applications. Numem aims to augment NASA’s High-Performance Spaceflight Computing (HPSC) program with design of radiation hardened & ultra-low power DNN Co-processor to enable AI applications. There is exponential increase in the use of sensors. These sensors and connected devices generate zettabytes of data per year. Machine learning with DNN capability is needed to extract meaningful and actionable information from this data. For some applications, the goal is to take immediate action based the data such as in robotics/drones, self-driving cars, smart Internet of Things whereas in other applications, the goal is to analyze and understand the data to identify trends as in case of surveillance, portable/wearable electronics. This radiation hardened Co-Processor will solidify HSPC avionics ecosystem with robust AI capabilities much needed for space autonomy, small sat constellations/autonomous science, human explorations and operations Habitat and deep space missions. On-board AI processing can enable spacecraft to efficiently process large volumes of raw sensor-data into scientific knowledge or actionable data to overcome limitations in downlink communication. On-board artificial intelligence can also enable spacecraft to formulate decisions for critical operations. Commercial applications This AI core comprises of reconfigurable DNN Engine with multiple compute units which can support multiple DNN models and sizes. Embedded STT-MRAM Memory which is 1000X high performance compared to FLASH memory and improves the silicon area by 2X to 3X compared to SRAM and reduces the standby-power by about 5X with radiation tolerant memory cell. This robust solution is crafted for low power machine vision, autonomous vehicles, facial recognition, healthcare, real-time tracking, agriculture, manufacturing. Radiation tolerant memory technology is ideal fit for space qualifications. Potential NASA Applications (Limit 1500 characters, approximately 150 words) AI Applications in Spacecraft, Lander, LEO Satellites, Lunar/Mars/Deep space missions, Planetary Real Time AI/ML Data Mining for Solar Flare, Planet Structure, Space Stations, Aerospace and Defense, Satellite Imagery Analysis, Global Surveillance Analysis, Near Earth Object Trajectory, Earth Climate prediction, Satellite Scans Analysis of Illegal Fishing in Oceans, Satellite Imagery on Deforestation, Satellite based Earth Observation Market Applications such as oil and gas industry, crop yield detection, pipeline leakage detection etc. Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words) All low power AI applications on Edge, Autonomous cars, IOT, Wearables, Mobile, Quantum Computing, Robotics, Drug Discovery, 5G, Particle Physics, Brain-Machine Interface,etc. Any DNN applications with need of low power vision classification, vision detection, speech recognition, natural language processing, audio recognition, social network filtering and machine translation are ideal fit.

Phase II

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Start Date: 00/00/00    Completed: 00/00/00
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