High performance cloud service for expressed sequence tag analysis = 발현 유전자 분석을 위한 고성능 클라우드 서비스 구축

Abstract

Computer-intensive biological applications are heavily reliant on the availability of computing resources. Grid based HPC clusters and emerging Cloud computing clusters provide a large scale computing environment for scientific users. However, large scale biological application often involves various types of computational tasks which can benefit from different types of computing clusters. Therefore, a high level job scheduling environment which integrates the Grid style HPC clusters and the Cloud computing clusters and manages jobs accordingly based on the characteristics of the jobs is required. In this paper, the authors propose a Web service framework for high-level job scheduling - Swarm. Swarm is developed for scientific applications that must submit massive number of high-throughput jobs or workflows to highly distributed computing clusters. Swarm allows the users to submit jobs to both Grid HPC and Cloud computing clusters. The Swarm service itself is designed to be extensible, lightweight, and easily installable on a desktop or a small server. As a Web service, derivative services based on Swarm can be straightforwardly integrated with Web portals and science gateways. This paper provides the motivation for this research, the architecture of the Swarm framework, and a performance evaluation of the system prototype.