Design and implementation of a cloud computing service for finite element analysis

• DOI: 10.1016/j.advengsoft.2012.10.003
• Publication Date: 2012-11-08T03:32:52Z
• Authors: Ismail Ari; Nitel Muhtaroglu
• Keywords: Task scheduling; Finite element analysis; 0202 electrical engineering, electronic engineering, information engineering; Cloud computing; 02 engineering and technology; Multi-core; SPOOLES; Structural mechanics

This paper presents an end-to-end discussion on the technical issues related to the design and implementation of a new cloud computing service for finite element analysis (FEA). The focus is specifically on performance characterization of linear and nonlinear mechanical structural analysis workloads over multi-core and multi-node computing resources. We first analyze and observe that accurate job characterization, tuning of multi-threading parameters and effective multi-core/node scheduling are critical for service performance. We design a ''smart'' scheduler that can dynamically select some of the required parameters, partition the load and schedule it in a resource-aware manner. We can achieve up to 7.53x performance improvement over an aggressive scheduler using mixed FEA loads. We also discuss critical issues related to the data privacy, security, accounting, and portability of the cloud service.