High-efficiency model calibration engine based on parallel computing

Abstract

Model calibration is key to model's practicality. Mathe matical models, which are widely used in environmental im pact assessment study to predict the quality of major com ponents of the environment, must be calibrated and vali dated so as to minimize errors in the prediction. Since in most cases, model calibration needs thousands of comput ing, the time efficiency becomes important. As computing performance is a key challenge in model calibration, the model calibration engine in the paper adopts multi-thread technology and a multiple-machine task scheduling based on a cluster of commodity machines to improve computing efficiency greatly. An improved scheduling algorithm is pro posed to ensure that the model calibration engine has a high efficiency on a cluster whose machines have diff erent com puting performance and running environment.