Sergio Paulo Caetano
Email
sa20ra202124015 at ajou.ac.kr
Research interests
Distributed Systems, Cloud Computing, Big Data (Processing and Analysis), Distributed Deep Learning, and AI
Introduction
Sergio Paulo Caetano is Ph.D. student in the Department of Artificial Intelligence at Ajou University
Publications
2024
3.
안성배,; 이재현,; 박종원,; Paulo, C. Sergio; 오상윤,
HPC 작업 수행 최적화를 위한 Autotuning 기법의 Surrogate Model 선택🇰🇷 DomesticConference
한국컴퓨터종합학술대회 (KCC 2024), 한국정보과학회, 2024.
@conference{kcc2024-1,
title = {HPC 작업 수행 최적화를 위한 Autotuning 기법의 Surrogate Model 선택},
author = {안성배 and 이재현 and 박종원 and C. Sergio Paulo and 오상윤},
url = {https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11862282},
year = {2024},
date = {2024-06-27},
urldate = {2024-06-27},
booktitle = {한국컴퓨터종합학술대회 (KCC 2024)},
publisher = {한국정보과학회},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
2.
Paulo, C. Sergio; 유미리,; 최지헌,; 오상윤,
Dynamic Programming-Based Multilevel Graph Partitioning for Large-Scale Graph Data🇰🇷 DomesticConference
2024년도 한국통신학회 동계종합학술발표회, 한국통신학회, 2024.
@conference{2024kics-2,
title = {Dynamic Programming-Based Multilevel Graph Partitioning for Large-Scale Graph Data},
author = {C. Sergio Paulo and 유미리 and 최지헌 and 오상윤},
url = {https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11737048},
year = {2024},
date = {2024-03-27},
booktitle = {2024년도 한국통신학회 동계종합학술발표회},
publisher = {한국통신학회},
abstract = {Multilevel graph algorithms are used to create optimal partitions for large graphs. However, the dynamic changes to the graph structures during partitioning lead to increased memory. These changes involve adding temporal data to arrays or queues during intermediary operations. To enhance efficiency and minimize memory usage, we integrated dynamic programming. Experimental results demonstrate the improved scalability and effectiveness of the proposed approach in terms of memory usage.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Multilevel graph algorithms are used to create optimal partitions for large graphs. However, the dynamic changes to the graph structures during partitioning lead to increased memory. These changes involve adding temporal data to arrays or queues during intermediary operations. To enhance efficiency and minimize memory usage, we integrated dynamic programming. Experimental results demonstrate the improved scalability and effectiveness of the proposed approach in terms of memory usage.
2023
1.
Baek, Minseok; Paulo, C. Sergio; Oh, Sangyoon
Analysis of the In-Memory Checkpointing Approach in Apache Flink🇰🇷 DomesticConference
2023년도 한국통신학회 하계종합학술발표회 , 한국통신학회 2023.
@conference{nokey,
title = {Analysis of the In-Memory Checkpointing Approach in Apache Flink},
author = {Minseok Baek and C. Sergio Paulo and Sangyoon Oh},
url = {https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11487634},
year = {2023},
date = {2023-06-21},
urldate = {2023-06-21},
booktitle = {2023년도 한국통신학회 하계종합학술발표회 },
organization = { 한국통신학회},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
