* 비전 Secure global leadership in AI data center system software through storage-driven I/O technologies, realize next-generation infrastructure capable of efficiently managing ultra-large-scale AI data on storage, and cultivate world-class system software researchers.
* 목표 Centering on the three core technologies required for ultra-low-latency storage utilization in large language models—storage-driven I/O, a CPU-GPU integrated file system, and a CPU-GPU integrated I/O operating system—this project aims to achieve a phased reduction of host software overhead and establish the capability to manage petabyte-scale AI data. Through this, the project seeks to move beyond the conventional CPU-centric I/O paradigm and establish novel system software technologies in which storage actively participates in the data path, thereby building a foundation for technological self-reliance in AI data center system software. Furthermore, by reducing dependence on costly GPU memory and lowering AI infrastructure deployment costs, strengthening the competitiveness of the domestic semiconductor and storage industry through technology transfer and open-source contributions, and improving AI infrastructure accessibility in the public sector, the project aims to promote the broad adoption of AI technologies across industry and society.
Hiring: Postdoctoral Researcher in Computer Science and Engineering (InnoCORE Project, MSIT)
The Storage Systems Research Center at KAIST (Director: Prof. Youjip Won) has open positions for a postdoctoral researcher in fields including, but not limited to, Operating Systems, Computer Architecture, and Mobile Computing, with an emphasis on GPU-centric computing system design.
These positions are fully funded by the InnoCORE project of the Ministry of Science and ICT (MSIT). KAIST is located in the beautiful city of Daejeon, Korea.
Participating faculty members are Prof. Youjip Won (http://oslab.kaist.ac.kr), Prof. John Dongjun Kim (http://icn.kaist.ac.kr), and Prof. Seulki Lee (https://sites.google.com/view/embeddedai) at KAIST. The applicant is expected to work closely with these members.
For further inquiry, please contact hyunjeong Lee (dongstar2@kaist.ac.kr) with your CV.
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