Abstract: A high performance computer system,e.g．a computer cluster,built for large-scale photorealistic rendering,i.e．render farm,is a basic infrastructure for producing CG animations and movie special effects．In a render farm,one of the key issues is the strategy of scheduling and dispatching rendering jobs,which greatly affects the computing efficiency．Time prediction for a render job plays an important and essential role in the job scheduling and dispatching stage．However,there is no feasible algorithm and even little research work on this problem．We focused on the Reyes rendering architecture．We first analyzed the factedors that affect the rendering time and extracted the seven key features as the feature vector based on the analysis．Then we proposed a time prediction framework based on AdaBoost.MH algorithm,in which we transformed the rendering time into intervals and combined them with the feature vector to obtain the samples．Experimental results show the effectiveness of the algorithm,and the accuracy of training set and test set is 79% and 78%．

Key words: Time prediction,AdaBoost.MH algorithm,Reyes rendering architecture,Render farm