Profile
Vertically Integrated Architecture Research Group (VIALab)
School of Electrical Engineering,
Korea Advanced Institute of Science and Technology (KAIST)
Email: yunjae408@kaist.ac.kr
Office: N1 818 @ KAIST
Education
Ph.D Student in School of Electrical Engineering, KAIST, 2021.03 ~ Present
Adviser: Prof. Minsoo Rhu
Master Student in School of Electrical Engineering, KAIST, 2019.03 ~ 2021.02
Adviser: Prof. Minsoo Rhu
Bachelor's Degree in Department of Electrical and Electronic Engineering, Yonsei university, 2013.03 ~ 2019.02
Summa Cum Laude
Recognition
The 27th Samsung Humantech Paper Award , 2021.02
Gold Prize (1st place in the Computer Science and Engineering track)
Scholar of the National Academic Excellence Scholarship for Engineering, Korea Student Aid Foundation (KOSAF), 2017.03 ~ 2018.12
Publication
Yunjae Lee*, Hyeseong Kim* and Minsoo Rhu, "PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models," The 51st International Symposium on Computer Architecture (ISCA-51), Buenos Aires, Argentina, June 2024
* Co-first authors
Acceptance Rate: 19% (83 among 423)
[Paper]
Hyeseong Kim*, Yunjae Lee*, and Minsoo Rhu, "FPGA-Accelerated Data Preprocessing for Personalized Recommendation Systems," IEEE Computer Architecture Letters (CAL), Nov. 2023
* Co-first authors
Yunjae Lee, Jinha Chung and Minsoo Rhu, "SmartSAGE: Training Large-scale Graph Neural Networks using In-Storage Processing Architectures," The 49th International Symposium on Computer Architecture (ISCA-49), New York, NY, June 2022
Acceptance Rate: 16% (67 among 400)
[Paper]
Yunjae Lee, Youngeun Kwon, and Minsoo Rhu, "Understanding the Implication of Non-Volatile Memory for Large-Scale Graph Neural Network Training," IEEE Computer Architecture Letters (CAL), Jul. 2021
[Paper]
Youngeun Kwon, Yunjae Lee, and Minsoo Rhu, "Tensor Casting: Co-Designing Algorithm-Architecture for Personalized Recommendation Training," The 27th IEEE International Symposium on High-Performance Computer Architecture (HPCA-27), Seoul, South Korea, Feb. 2021
Acceptance Rate: 24% (63 among 258)
[Paper]
Youngeun Kwon, Yunjae Lee, and Minsoo Rhu, "TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning," The 52nd IEEE/ACM International Symposium on Microarchitecture (MICRO-52), Columbus, OH, Oct. 2019
Selected for IEEE Micro Top Picks Honorable Mention ("IEEE Micro - The 2019 Top Picks in Computer Architecture")
Acceptance Rate: 22% (79 among 344)
[Paper]
Patents
Inventor: Minsoo Rhu, Youngeun Kwon, and Yunjae Lee
Applications: KR (2019), US (2020), CN (2020)
Registered: KR (2022)
Current Assignee: KAIST