A Risk Evaluation Model of PC Cluster with Seismic Data Processing
Feixue Huang, Zhijie Li, Xiaoli Sun · 2009
This study's objective is to solve performance evaluation problem of PC cluster in processing seismic data intensive computing. The objective of performance evaluation is determining the relationship between the number of PC node and the scale of tasks to be processed to decide whether the transaction of seismic data processing should be transformed from mainframe computer to PC cluster platform. In particular, this paper presented a model based on least-squares regression for evaluating the performance of PC cluster. The model begins with the comparison of the computing performance of PC clusters by collecting experiential data, and proceeded by establishing performance evaluation model of PC cluster using least-squares regression, as well as performing error analysis and significance test. To study the effects of the proposed model, a series of experiments based on PC cluster are designed and implemented. The results show that the computational efforts, communication traffic and their relationship play an important role in task processing of PC cluster. This study's conclusions indicate that PC cluster can be substituted for mainframe computer in order to save the expense of processing seismic data.