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Enhancing hybrid cloud ray clusters: automated data management and innovative networking for efficient HPC cloud bursting
Zhu, Zhongbo
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https://hdl.handle.net/2142/124427
Description
- Title
- Enhancing hybrid cloud ray clusters: automated data management and innovative networking for efficient HPC cloud bursting
- Author(s)
- Zhu, Zhongbo
- Issue Date
- 2024-04-30
- Director of Research (if dissertation) or Advisor (if thesis)
- Kindratenko, Volodymyr
- Department of Study
- Electrical & Computer Eng
- Discipline
- Electrical & Computer Engr
- Degree Granting Institution
- University of Illinois at Urbana-Champaign
- Degree Name
- M.S.
- Degree Level
- Thesis
- Keyword(s)
- Distributed Systems
- Cloud Computing
- High Performance Computing
- Distributed Machine Learning
- Abstract
- The increasing reliance on hybrid systems that combine High-Performance Computing (HPC) and Cloud computing reflects their ability to manage workload surges and reduce users' queuing time. This thesis presents the development of an innovative HPC-Cloud bursting system, which leverages the Ray open-source distributed framework. Our system features an advanced automated data management mechanism and a unique dynamic label-based scheduling algorithm that intelligently manages data dependencies and minimizes data transmission overheads. My personal contributions to this project were critical in several areas: I designed and implemented network solutions and infrastructure as code, significantly simplifying the deployment and operational management of the hybrid system while also reducing costs. Additionally, I played an important role in optimizing the system's scheduler to improve stability and contributed directly to a performance boost. Our benchmarks, which focus on machine learning model training and image processing tasks, demonstrate our system's enhanced efficiency, achieving up to 20\% improvement when compared to traditional methods.
- Graduation Semester
- 2024-05
- Type of Resource
- Thesis
- Copyright and License Information
- Copyright 2024 Zhongbo Zhu
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Graduate Dissertations and Theses at Illinois PRIMARY
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