E-LIB Suche - Ergebnisse für: Choi, Hyeonseong

1

EDDIS: Accelerating Distributed Data-Parallel DNN Training ..:

, In: 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW),

Ahn, Shinyoung ; Ahn, Hooyoung ; Choi, Hyeonseong. - p. 1167-1168 , 2024

Link: https://doi.org/10.1109/..

2

Towards accelerating model parallelism in distributed deep ..:

Choi, Hyeonseong ; Lee, Byung Hyun ; Chun, Se Young..
PLOS ONE. 18 (2023) 11 - p. e0293338 , 2023

Link: https://doi.org/10.1371/..

3

Efficient Use of GPU Memory for Large-Scale Deep Learning M..:

Choi, Hyeonseong ; Lee, Jaehwan
Applied Sciences. 11 (2021) 21 - p. 10377 , 2021

Link: https://doi.org/10.3390/..

4

Towards an optimized distributed deep learning framework fo..:

Kim, Youngrang ; Choi, Hyeonseong ; Lee, Jaehwan...
Cluster Computing. 23 (2020) 3 - p. 2287-2300 , 2020

Link: https://doi.org/10.1007/..

5

Communication Optimization Schemes for Accelerating Distrib..:

Lee, Jaehwan ; Choi, Hyeonseong ; Jeong, Hyeonwoo..
Applied Sciences. 10 (2020) 24 - p. 8846 , 2020

Link: https://doi.org/10.3390/..

6

Empirical Performance Analysis of Collective Communication ..:

Woo, Junghoon ; Choi, Hyeonseong ; Lee, Jaehwan
Applied Sciences. 10 (2020) 19 - p. 6717 , 2020

Link: https://doi.org/10.3390/..

7

Diagnostic Assessment Generation via Combinatorial Search:

Kim, Daehan ; Choi, Hyeonseong ; Jung, Guik
http://arxiv.org/abs/2112.11188. , 2021

Link: http://arxiv.org/abs/211..

8

Training when the size of the micro-batch is too large:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g003. , 2023

Link: https://doi.org/10.1371/..

9

Model parallelism with pipelining technique:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g002. , 2023

Link: https://doi.org/10.1371/..

10

Graph of throughput change with a mini-batch size:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g006. , 2023

Link: https://doi.org/10.1371/..

11

Towards accelerating model parallelism in distributed deep ..:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621816/?tool=EBI. , 2023

Link: https://doaj.org/article..

12

Training performance when batch normalization and group nor..:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g009. , 2023

Link: https://doi.org/10.1371/..

13

Reduction of training time by applying pipelining technique:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g001. , 2023

Link: https://doi.org/10.1371/..

14

Training when the size of the micro-batch is too small:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g004. , 2023

Link: https://doi.org/10.1371/..

15

Training performance when batch normalization is applied in..:

Hyeonseong Choi ; Byung Hyun Lee ; Se Young Chun.
doi:10.1371/journal.pone.0293338.g007. , 2023

Link: https://doi.org/10.1371/..