The CEITRES@UCR (IRES) program supported a cohort of four UCR students for the summer of 2019.

The cohort consisted of five undergraduate students (Michael O'dea  (CEN Major), Jonathan Clarke (CEN Major), Cindy Ho (Female, CS Major), Christian Campos (CS Major),  Ally Thach (Female, CS Major),  Abraham Park (CEN Major)). Cindy Ho quit the program due to covid-19 impact on her family. 

All the students first went through the 3 month training by auditing the EE260 (Hardware Design For Machine Learning) in the Spring 2020. They all also enrolled in the EE190 (special study) in Spring 2020 as part of training process. Then all the students spent 10 weeks in the summer working on the different research topics.  Due to the covid-19 pandemic impacts and travel restriction, all the IRES students work remotely from home for the summer 2020. 

Collaborative research work:

During the program, the students conducted cutting edge research in applying machine learning to solve several problems in VLSI design automation with focus on the reliability and thermal related issues in VLSI design. Namely, the students helped with the ongoing development of a machine learning based thermal modeling scheme that can be used for post-silicon thermal characterization of commercial high-performance microprocessors. With the aforementioned thermal model, the students further aided in the development of a dynamic thermal/power control scheme by exploiting the dynamic-voltage-and-frequency-scaling control knobs that are available in Intel core processors. Additionally, the students explored GPU based brain-inspired hyperdimentional computing for classification task. 

Social and career development:

Due to the impacts of covid-19 pandemic,  the social activities in the 2020 program is limited. Students mainly participated in the Zoom meetings and also remotely worked with Senior  PhD students in VSCLAB during the summer 2020.

Published co-authored paper by IRES students:

1.        J. Zhang, S. Sadiqbatcha, Y. Gao, M. O’Dea, N. Yu, and S. X.-D. Tan, “HAT-DRL: Hotspot-Aware Task Mapping for Lifetime Improvement of Multicore System using Deep Reinforcement Learning”, Proc. 2nd IEEE/ACM Workshop on Machine Learning for CAD (MLCAD’20), Virtual Event, Nov. 2020
2.          J. Zhang,  S. Sadiqbatcha,  M. O’Dea, H. Amrouch and S. X.-D. Tan, “Full-chip power density and thermal map characterization for commercial micrprocessors under heat sink cooking”,  IEEE Transaction on Computer-Aided Design of Integrated Circuits and Systems (TCAD),  accepted.