high level synthesis for machine learning (previously hls4ml)
Description
This project develops hardware-software AI codesign tools for FPGAs and ASICs for algorithms running at the extreme edge.
Detailed example
It can be an AI algorithm from prediction to data compression to control (decision making).
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
hls4ml is used to implement specialized AI algorithms in embedded hardware. This is valuable across a wide range of scientific applications for enabling real-time processing capabilitles. This can accelerate sientific discovery and time to science thus enabling large cost savings and DOE scientific prestige.
Audit / financial statement impact
The use case does not have an effect on civil rights/liberties/privacy, access to education/housing/insurance/credit/employment, access to critical government resources/services, human health/safety, critical infrastructure/public safety
Controls / human review
ATO: No; PIA: Not published
Data needed
research datasets from scientific experiments