빅데이터 분석 및 머신러닝 서비스 제공을 위한 컨테이너 기반 HPC 클러스터 구축 방안

• 영문명: Container-based HPC Cluster System for BigData Analysis and Machine Learning Applications
• 발행기관: 한국산업경영시스템학회
• 저자명: 박주원(Ju-Won Park) 이승민(Seungmin Lee)
• 간행물 정보: 『한국산업경영시스템학회 학술대회』2019년 추계학술대회 논문집, 156~159쪽, 전체 4쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2019.10.30

영문 초록

Several fields of basic sciences such as meteorology, chemistry, and high-energy physics have required large-scale workloads. To support it, a high-performance system (HPC), which is optimized for parallel computing is widely used. Recently, due to the fourth industrial revolution, HPC computing resources are increasing demands in computer science fields such as big data analysis and machine learning. To support these new services, the existing HPC system has big troubles such as rigid SW configuration, high maintenance cost, and limited job type support. In this paper, we propose a container-based HPC cluster system architecture to solve these problems. The presented system architecture is used Docker for container execution and kubernetes as the container orchestration toolkit.

목차

Abstract

1. 서론

2. 컨테이너 기반 클러스터 시스템

3. 결론

참고문헌

키워드

Container Kubernetes High Performance Computing