{"id":197304,"date":"2025-06-20T15:23:44","date_gmt":"2025-06-20T06:23:44","guid":{"rendered":"http:\/\/ee.presscat.kr\/?post_type=research-achieve&p=197304"},"modified":"2026-04-13T03:48:41","modified_gmt":"2026-04-12T18:48:41","slug":"professors-myoungsoo-jungs-team-reveals-their-works-on-next-generation-interconnect-semiconductor-technologies-in-ieee-micro","status":"publish","type":"research-achieve","link":"http:\/\/ee.presscat.kr\/en\/research-achieve\/professors-myoungsoo-jungs-team-reveals-their-works-on-next-generation-interconnect-semiconductor-technologies-in-ieee-micro\/","title":{"rendered":"Professors Myoungsoo Jung\u2019s Team Reveals Their Works on Next-Generation Interconnect\/Semiconductor Technologies in IEEE Micro."},"content":{"rendered":"
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\u3008Professor Myoungsoo Jung\u2019s Research Team \u3009<\/span><\/figcaption><\/figure>\n

Professor Myoungsoo Jung\u2019s research team is going to reveal their works on next-generation interconnect \/ semiconductor technologies in IEEE Micro<\/em>, a leading journal in computer architecture.<\/span><\/p>\n

IEEE Micro<\/em>, established in 1981, is a bimonthly publication featuring recent advances in computer architecture and semiconductor technologies. Professor Jung\u2019s team will present a total of five papers in the upcoming May-June issue on \u201cCache Coherent Interconnects and Resource Disaggregation Technology\u201d.<\/span><\/p>\n

Among them, three papers focus on applying Compute Express Link (CXL) to storage systems. Especially, the team introduces solutions to improve the performance of CXL-SSD, a concept for which Professor Jung suggested a practical implementation in early 2022. These technologies enable memory expansion through large-capacity SSDs while providing performance comparable to DRAM.<\/span><\/p>\n

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\"<IEEE
\u3008List of Papers to Be Published in IEEE Micro\u3009<\/figcaption><\/figure>\n

The team also explored storage architectures incorporating In-Storage Processing (ISP), which performs computation directly inside the storage pool. By processing data within storage, this approach reduces data movement and thereby improves efficiency in large-scale applications such as large language models (LLMs).<\/span><\/p>\n

These papers, conducted in collaboration with the faculty-led startup Panmnesia, will be published through\u00a0IEEE Micro<\/em>\u2019s official website and in its regular print issue.<\/span><\/p>\n

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\u203b Click on the title to view the early access link.<\/strong><\/span><\/div>\n