Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Wooseok Chang"'
Autor:
Hamin Jang, Taehun Kang, Joonsung Kim, Jaeyong Cho, Jae-Eon Jo, Seungwook Lee, Wooseok Chang, Jangwoo Kim, Hanhwi Jang
Publikováno v:
IEEE Computer Architecture Letters. 21:25-28
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c21920dd066be38fd0a24930b3935504
https://doi.org/10.1109/lca.2022.3168831
https://doi.org/10.1109/lca.2022.3168831
Autor:
Ihor Vasyltsov, Wooseok Chang
Publikováno v:
Transactions on Computational Science and Computational Intelligence ISBN: 9783030702953
In this paper we propose a method to approximate softmax layer for computer vision applications, especially on the devices with limited hardware (HW) resources, such as mobile or edge platforms. In this paper we showed that using a max-normalization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::928b975f08cc5fb1d5d8ce6dd70e06c7
https://doi.org/10.1007/978-3-030-70296-0_41
https://doi.org/10.1007/978-3-030-70296-0_41
Publikováno v:
2017 Computing Conference.
For Cloud computing services, efficient task management to sustain I/O requests with latency outliers reduced is an important design requirement for QoS. However, the existing task management techniques do not adequately meet this requirement on mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8dbcfcd8a6052493cfbe40a0fe6e7956
https://doi.org/10.1109/sai.2017.8252106
https://doi.org/10.1109/sai.2017.8252106
Autor:
Wooseok Chang, Sayan Goswami, Kisung Lee, Jaeki Hong, A. Das, Seung-Jong Park, Richard Platania, Ling Liu
Publikováno v:
CLOUD
High-performance analysis of big data demands more computing resources, forcing similar growth in computation cost. So, the challenge to the HPC system designers is providing not only high performance but also high performance at lower cost. For high
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17338ebcb2cbdb011564c61be7189d98
https://doi.org/10.1109/cloud.2017.27
https://doi.org/10.1109/cloud.2017.27
Publikováno v:
SAC
The ever increasing demand of effective resource utilization in data centers has resulted in the dramatic development of various virtualization environments. Furthermore, the requirements on rapid processing of large data has not only caused to the r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75b32a40962be0025f4dbf397bdadb09
https://doi.org/10.1145/2851613.2851739
https://doi.org/10.1145/2851613.2851739
Publikováno v:
Middleware Posters and Demos
For container-based virtualization such as Linux container (LXC), efficient and proportional resource sharing is an important design requirement. However, existing container resource management techniques do not adequately meet this requirement on mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd90db2a646a58f4420a47835470d9e6
https://doi.org/10.1145/2830894.2830901
https://doi.org/10.1145/2830894.2830901
Publikováno v:
IEEE BigData
Scientists are increasingly using the current state of the art big data analytic software (e.g., Hadoop, Giraph, etc.) for their data-intensive applications over HPC environment. However, understanding and designing the hardware environment that thes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f5dace4742a345de1b6c14d9ca0b639
https://doi.org/10.1109/bigdata.2015.7363750
https://doi.org/10.1109/bigdata.2015.7363750
Publikováno v:
BigData Congress
BigData manipulates a massive volume of data for which the traditional techniques are not effective. Apache Hadoop is currently a most popular software framework supporting BigData analysis. As the scale of Hadoop cluster grows larger, building Hadoo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a299669e3d37a6bcd89205dedb4c49a
https://doi.org/10.1109/bigdata.congress.2014.90
https://doi.org/10.1109/bigdata.congress.2014.90