2011 | OriginalPaper | Chapter
Scheduling Concurrent Workflows in HPC Cloud through Exploiting Schedule Gaps
Authors : He-Jhan Jiang, Kuo-Chan Huang, Hsi-Ya Chang, Di-Syuan Gu, Po-Jen Shih
Published in: Algorithms and Architectures for Parallel Processing
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Many large-scale scientific applications are usually constructed as workflows due to large amounts of interrelated computation and communication. Workflow scheduling has long been a research topic in parallel and distributed computing. However, most previous research focuses on single workflow scheduling. As cloud computing emerges, users can now have easy access to on-demand high performance computing resources, usually called HPC cloud. Since HPC cloud has to serve many users simultaneously, it is common that many workflows submitted from different users are running concurrently. Therefore, how to schedule concurrent workflows efficiently becomes an important issue in HPC cloud environments. Due to the dependency and communication costs between tasks in a workflow, there usually are gaps formed in the schedule of a workflow. In this paper, we propose a method which exploits such schedule gaps to efficiently schedule concurrent workflows in HPC cloud. The proposed scheduling method was evaluated with a series of simulation experiments and compared to the existing method in the literature. The results indicate that our method can deliver good performance and outperform the existing method significantly in terms of average makespan, up to 18% performance improvement.