Towards Edge Computing: A Software and Hardware Co-Design Methodology for Application-Specific Integrated Circuit (ASIC)-based Scientific Neuromorphic Computing (NC)
Department of Energy · BNL - Brookhaven National Laboratory (SC43 OIM)
Overview
- Development stage
- In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Does not meet definition
- Start date
- Not reported
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
One project: Current deep neural network (DNN)-based Artificial Intelligence (AI) algorithms have already been successfully applied to particle physics applications. This project will develop a co-design approach for methodologies and their implement
Expected benefits
One project: Current deep neural network (DNN)-based Artificial Intelligence (AI) algorithms have already been successfully applied to particle physics applications. This project will develop a co-design approach for methodologies and their implementation of edge computing for optimal handling of data streams
System outputs
One project: Current deep neural network (DNN)-based Artificial Intelligence (AI) algorithms have already been successfully applied to particle physics applications. This project will develop a co-design approach for methodologies and their implementation of edge computing for optimal handling of data streams
Technology
- AI classification
- Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
- System name(s)
- Not reported
- Custom-developed code
- Not reported
- Public source code
- Not reported
Sourcing
- How it was built
- Not reported
- Vendor (as reported)
- Not reported
- Vendors (standardized)
- None on the standard list
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- Not reported
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Not reported
- Demographic features
- Not reported
- Training and evaluation data
- Not reported
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Potential impacts and how they were identified
Not reported