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pro vyhledávání: '"Yu-MinChen"'
Autor:
Li, Suyi, Lu, Hanfeng, Wu, Tianyuan, Yu, Minchen, Weng, Qizhen, Chen, Xusheng, Shan, Yizhou, Yuan, Binhang, Wang, Wei
Pre-trained large language models (LLMs) often need specialization for domain-specific tasks. Low-Rank Adaptation (LoRA) is a popular approach that adapts a base model to multiple tasks by adding lightweight trainable adapters. In this paper, we pres
Externí odkaz:
http://arxiv.org/abs/2401.11240
Autor:
Yu, Minchen, Wang, Ao, Chen, Dong, Yu, Haoxuan, Luo, Xiaonan, Li, Zhuohao, Wang, Wei, Chen, Ruichuan, Nie, Dapeng, Yang, Haoran
Serverless computing has become increasingly popular for machine learning inference. However, current serverless platforms lack efficient support for GPUs, limiting their ability to deliver low-latency inference. In this paper, we propose FaaSwap, a
Externí odkaz:
http://arxiv.org/abs/2306.03622
Serverless applications are typically composed of function workflows in which multiple short-lived functions are triggered to exchange data in response to events or state changes. Current serverless platforms coordinate and trigger functions by follo
Externí odkaz:
http://arxiv.org/abs/2109.13492
Autor:
Yu-MinChen, 陳育民
100
Nowadays the semiconductor industry, being the focal industry in Taiwan, has to cope with the fast growing technology development, high cost consideration and increase in wafer sizes and weight, which have caused the long-distance material m
Nowadays the semiconductor industry, being the focal industry in Taiwan, has to cope with the fast growing technology development, high cost consideration and increase in wafer sizes and weight, which have caused the long-distance material m
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/35549248108066535342
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