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비휘발성 메모리의 동적 활용을 통한 서버 시스템 성능 및 사용성 향상
송현호(Hyeonho Song),노삼혁(Sam H. Noh) Korean Institute of Information Scientists and Eng 2021 정보과학회논문지 Vol.48 No.10
Persistent Memory (PM) has been studied assuming that it can only be used as main memory, storage, or storage cache. In this paper, we present HMMS (Hybrid Memory Management System), which is a memory management system that allows PM to play all these roles, not exclusively, but simultaneously. Specifically, HMMS dynamically and appropriately allocates these three roles by reflecting the state of the computing system and the users’ requests. With HMMS, we aim to improve the functionality and performance of computing systems where DRAM and PM coexist.
송현호(Hyeonho Song),박건우(Kunwoo Park),차미영(Meeyoung Cha) Korean Institute of Information Scientists and Eng 2020 정보과학회논문지 Vol.47 No.12
This study presents an embedding method that effectively learns emote’s meaning in Twitch.tv to understand the audience reaction in live streaming. The proposed method first trains an embedding matrix for text and emotes, respectively, and merges the two matrices into one. Using 2,220,761 clips shared on Twitch.tv, this study conducted two experiments: clustering and clip popularity prediction. Results showed that the approach identifies emote clusters that express a similar emotion and detects popular clips. Future studies could utilize the proposed emote embedding method for the highlight prediction of a live stream.