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pro vyhledávání: '"Dayapule, Sai Santosh"'
Autor:
Gogineni, Kailash, Dayapule, Sai Santosh, Gómez-Luna, Juan, Gogineni, Karthikeya, Wei, Peng, Lan, Tian, Sadrosadati, Mohammad, Mutlu, Onur, Venkataramani, Guru
Reinforcement Learning (RL) trains agents to learn optimal behavior by maximizing reward signals from experience datasets. However, RL training often faces memory limitations, leading to execution latencies and prolonged training times. To overcome t
Externí odkaz:
http://arxiv.org/abs/2405.03967
Autor:
Dayapule, Sai Santosh, Nguyen, Kathy, Kahl, Gregory, Subramaniam, Suresh, Venkataramani, Guru
Data centers have become a popular computing platform for various applications, and they account for nearly 2% of total US energy consumption. Therefore, it has become important to optimize data center power, and reduce their energy footprint. Most e
Externí odkaz:
http://arxiv.org/abs/2111.15502
Autor:
Yao, Fan, Ngyugen, Kathy, Dayapule, Sai Santosh, Wu, Jingxin, Lu, Bingqian, Subramaniam, Suresh, Venkataramani, Guru
Cloud computing based systems, that span data centers, are commonly deployed to offer high performance for user service requests. As data centers continue to expand, computer architects and system designers are facing many challenges on how to balanc
Externí odkaz:
http://arxiv.org/abs/1909.13548
Autor:
Fang, Hongyu1 (AUTHOR) hongyufang_ee@gwu.edu, Dayapule, Sai Santosh1 (AUTHOR) saisantoshd@gwu.edu, Yao, Fan1 (AUTHOR) albertyao@email.gwu.edu, Doroslovački, Miloš1 (AUTHOR) doroslov@email.gwu.edu, Venkataramani, Guru1 (AUTHOR) guruv@gwu.edu
Publikováno v:
International Journal of Parallel Programming. Aug2019, Vol. 47 Issue 4, p571-594. 24p.
Akademický článek
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