Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Yeonhong Park"'
Recently, Graph Neural Networks (GNNs) have been receiving a spotlight as a powerful tool that can effectively serve various inference tasks on graph structured data. As the size of real-world graphs continues to scale, the GNN training system faces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffbe666e1581132592a2ed7577d77a7e
http://arxiv.org/abs/2208.09151
http://arxiv.org/abs/2208.09151
Publikováno v:
Proceedings of the 59th ACM/IEEE Design Automation Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb511989fb19fa3d549fc98740bc36a5
https://doi.org/10.1145/3489517.3530564
https://doi.org/10.1145/3489517.3530564
Autor:
Michael Jaemin Kim, Jaehyun Park, Yeonhong Park, Wanju Doh, Namhoon Kim, Tae Jun Ham, Jae W. Lee, Jung Ho Ahn
Publikováno v:
2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA).
Since its public introduction in the mid-2010s, the Row Hammer (RH) phenomenon has drawn significant attention from the research community due to its security implications. Although many RH-protection schemes have been proposed by processor vendors,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::233ed5442534812b3eaa489e83d5b478
https://doi.org/10.1109/hpca53966.2022.00088
https://doi.org/10.1109/hpca53966.2022.00088
Publikováno v:
ISCA
Search is one of the most popular and important web services. The inverted index is the standard data structure adopted by most full-text search engines. Recently, custom hardware accelerators for inverted index search have emerged to demonstrate muc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3479e4e477cc7e6f2abe5a96ff7c56e
https://doi.org/10.1109/isca52012.2021.00030
https://doi.org/10.1109/isca52012.2021.00030
Autor:
Jongsung Lee, Jonghyun Bae, Jae W. Lee, Yeonhong Park, Sam Son, Young H. Oh, Tae Jun Ham, Seonghak Kim, Yunho Jin, Dong Uk Kim
Publikováno v:
HPCA
To meet surging demands for deep learning inference services, many cloud computing vendors employ high-performance specialized accelerators, called neural processing units (NPUs). One important challenge for effective use of NPUs is to achieve high r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d5df2e54daa56f09269fd0c21c4473a
https://doi.org/10.1109/hpca51647.2021.00056
https://doi.org/10.1109/hpca51647.2021.00056
Publikováno v:
MICRO
Row Hammer is a serious security threat to modern computing systems using DRAM as main memory. It causes charge loss in DRAM cells adjacent to a frequently activated aggressor row and eventually leads to data bit flips in those cells. Even with count
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec80f54f1117c58b0d5973b8a287686f
https://doi.org/10.1109/micro50266.2020.00014
https://doi.org/10.1109/micro50266.2020.00014
Autor:
Deog-Kyoon Jeong, Young H. Oh, Seonghak Kim, Sung Jun Jung, Kyoung Tae Park, Jung-Hun Park, Jae W. Lee, Tae Jun Ham, Sang Hee Lee, Yeonhong Park, Yoonho Song
Publikováno v:
HPCA
With the increasing computational demands of neural networks, many hardware accelerators for the neural networks have been proposed. Such existing neural network accelerators often focus on popular neural network types such as convolutional neural ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63050d9ff0abfb7bc9b63b9d3ee9e688
https://doi.org/10.1109/hpca47549.2020.00035
https://doi.org/10.1109/hpca47549.2020.00035