Title:
On the learning of surrogate models in AI powered design automation
Agreement Value:
$158,070.00
Agreement Date:
Nov 24, 2020 - Jun 1, 2023
Description:
Al-powered design automation inevitably involves iterations between generating a candidate design and evaluating its quality. As a result, rapid evaluation of the candidate designs is critically needed. In practice, however, evaluating the quality of a design is usually carried out by a physical process that is resource intensive and/or time consuming. As such, this resource and time consumption can be a major bottleneck for Al-powered design automations. To overcome this limitation, a surrogate evaluation function or a "surrogate model", is often used to replace the evaluation process and a learning approach is taken to estimate the parameters of the model. More specifically, the surrogate model is learned from a set of designs for which quality measurements have been obtained from the original evaluation process. This Project focuses on studying the effectiveness and robustness of such a learning approach and developing novel methods for this purpose.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Ottawa, Ontario, CA K1N 6N5
Reference Number:
172-2020-2021-Q3-962389
Report Type:
Grants and Contributions
Recipient Business Number:
119278877
Additional Information:
Belated reporting: This agreement has been amended 1 time(s). The end date of this agreement has been modified by 181 days.
Amendment Date
Aug 31, 2022
Recipient's Legal Name:
University of Ottawa
Federal Riding Name:
Ottawa–Vanier
Federal Riding Number:
35078
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.