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

Abstract

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 7.53× 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.