Juncheng Gu - Google Scholar
WEBJ Gu. 2021. Articles 1–11. Systems Research Engineer at Google - Cited by 1,226 - Machine Learning Systems - Computer Systems - Rack-Scale Computing - Green Computing.
Juncheng Gu - Computer Systems for Machine Learning
WEBMar 9, 2024 · My research interests are broadly in computer systems and networking, especially in machine learning systems, operating systems, and resource management. Throughout my Ph.D. study, I mainly explored how to build an efficient deep learning cluster relying on low-latency RDMA networks (thesis).
Juncheng Gu - Google - LinkedIn
WEBView Juncheng Gu’s profile on LinkedIn, a professional community of 1 billion members. I am working on building efficient software systems for LLMs at SystemsResearch@Google. I…
- Connections: 374
- Location: Google
WEBJUNCHENG GU. 11664 179th Pl NE, Redmond, WA 98052. http://gujuncheng.info. Email: [email protected] Phone: (+1) 352-281-9623. Research Interests. I am broadly interested in computer systems and networking, especially in operating systems, virtualization, and resource management.
Juncheng Yang's website
WEBAssistant Professor (Starting Fall 2025) School of Engineering and Applied Science, Harvard University. juncheng # g.harvard.edu. 150 Western Ave, Allston, MA, 02134. I am an Assistant Professor in the Computer Science Division in School of Applied Science and Engineering at Harvard University.
Juncheng Gu - PhD - EECS - UMich
WEBJuncheng Gu - PhD - EECS - UMich
Efficient Resource Management for Deep Learning Clusters
WEBGu, Juncheng. 2021. View/ Open. jcgu_1.pdf. (4MB. PDF) Abstract. Deep Learning (DL) is gaining rapid popularity in various domains, such as computer vision, speech recognition, etc. With the increasing demands, large clusters have been built to develop DL models (i.e., data preparation and model training). DL jobs have s ... [more] Deep Blue DOI.
Efficient Memory Disaggregation with Infiniswap - USENIX
WEBJuncheng Gu, Youngmoon Lee, Yiwen Zhang, Mosharaf Chowdhury, and Kang Shin, University of Michigan. Abstract: Memory-intensive applications suffer large performance loss when their working sets do not fully fit in memory.
Junchen Gu - AstraZeneca - LinkedIn
WEBNov 28, 2023 · About. Computational scientist aspired to discover clinically meaningful and actionable insights… Experience. AstraZeneca. Waltham, Massachusetts, United States. - Greater New York City Area. -...
- 500+ connections
- Location: AstraZeneca
Juncheng Hu - dblp
WEBSep 14, 2024 · Juncheng Hu, Chunbao Mo: Development and Application of a Machine Learning-Based Prediction Model for 6-Month Unplanned Readmission in Heart Failure Patients. HCI (27) 2024: 271-279
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