Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Chun‐Gi Lyuh"'
Publikováno v:
ETRI Journal, Vol 46, Iss 5, Pp 817-828 (2024)
Owing to the widespread advancement of transformer-based artificial neural networks, artificial intelligence (AI) processors are now required to perform matrix-vector multiplication in addition to the conventional matrix-matrix multiplication. Howeve
Externí odkaz:
https://doaj.org/article/0908f63293204195ba8eabaaddf15ce6
Publikováno v:
ETRI Journal, Vol 46, Iss 5, Pp 839-850 (2024)
As computing systems become increasingly larger, high-performance comput-ing (HPC) is gaining importance. In particular, as hyperscale artificial intelli-gence (AI) applications, such as large language models emerge, HPC has become important even in
Externí odkaz:
https://doaj.org/article/d13945cf961545b3becd167f104a2b89
Autor:
Jaehoon Chung, HyunMi Kim, Kyoungseon Shin, Chun-Gi Lyuh, Yong Cheol Peter Cho, Jinho Han, Youngsu Kwon, Young-Ho Gong, Sung Woo Chung
Publikováno v:
ETRI Journal, Vol 44, Iss 5, Pp 849-858 (2022)
Dynamic voltage frequency scaling (DVFS) has been widely adopted for runtime power management of various processing units. In the case of neural processing units (NPUs), power management of neural network applications is required to adjust the freque
Externí odkaz:
https://doaj.org/article/7019db6b66c447488c26803a9450cb76
Autor:
Yong Cheol Peter Cho, Jaehoon Chung, Jeongmin Yang, Chun‐Gi Lyuh, HyunMi Kim, Chan Kim, Je‐seok Ham, Minseok Choi, Kyoungseon Shin, Jinho Han, Youngsu Kwon
Publikováno v:
ETRI Journal, Vol 42, Iss 4, Pp 491-504 (2020)
We present AB9, a neural processor for inference acceleration. AB9 consists of a systolic tensor core (STC) neural network accelerator designed to accelerate artificial intelligence applications by exploiting the data reuse and parallelism characteri
Externí odkaz:
https://doaj.org/article/b38d7df90356434ebdad7b6280b1415f
Publikováno v:
ETRI Journal, Vol 42, Iss 4, Pp 505-517 (2020)
The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high‐performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high‐performance accele
Externí odkaz:
https://doaj.org/article/dd2649a76470442fa7657e9ac84b2695
Autor:
Won Jeon, Yong Cheol Peter Cho, Hyun Mi Kim, Hyeji Kim, Jaehoon Chung, Juyeob Kim, Miyoung Lee, Chun-Gi Lyuh, Jinho Han, Youngsu Kwon
Publikováno v:
2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::683ecbc6648515e4d7dab3062d41b407
https://doi.org/10.1109/aicas54282.2022.9869984
https://doi.org/10.1109/aicas54282.2022.9869984
Autor:
Jinho Han, Chun-Gi Lyuh, Kyeongsun Shin, Hyun Mi Kim, Hyunjeong Kwon, Jaehoon Chung, Cheol Peter Cho, Jinkyu Kim, Jeonghui Suk, Chan Kim, Minseok Choi, Youngsu Kwon
Publikováno v:
2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da33a942aa067de69fb7dec5612fa351
https://doi.org/10.1109/aicas54282.2022.9869983
https://doi.org/10.1109/aicas54282.2022.9869983
Publikováno v:
2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca9c4a77a364cae1f8a18c184ffc5205
https://doi.org/10.1109/aicas54282.2022.9869913
https://doi.org/10.1109/aicas54282.2022.9869913
Autor:
Hyun-Mi Kim, Jinho Han, Minseok Choi, Je-Seok Ham, Chan Kim, Kyoung-Seon Shin, Jeongmin Yang, Young-Su Kwon, Yong Cheol Peter Cho, Chun-Gi Lyuh, Jaehoon Chung
Publikováno v:
ETRI Journal, Vol 42, Iss 4, Pp 491-504 (2020)
We present AB9, a neural processor for inference acceleration. AB9 consists of a systolic tensor core (STC) neural network accelerator designed to accelerate artificial intelligence applications by exploiting the data reuse and parallelism characteri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ef0057f1f8dfc07bd921b88950bac39
https://doi.org/10.4218/etrij.2020-0134
https://doi.org/10.4218/etrij.2020-0134
Publikováno v:
ETRI Journal, Vol 42, Iss 4, Pp 505-517 (2020)
The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high‐performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high‐performance accele
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cbafa4ee082cb4247dfed2573ab2bb2
https://doaj.org/article/dd2649a76470442fa7657e9ac84b2695
https://doaj.org/article/dd2649a76470442fa7657e9ac84b2695