The accurate and fast calculation of transcriptome expression level plays an important role in transcriptome research. Based on the previously devised Gamma model for exon array data (GME), a parallel computing method is proposed to improve the computational efficiency of GME on large scale Affymetrix exon chip datasets by taking full advantage of multi-core or cluster computation environment. The princi ples of the GME model and the parallel computing strategy are introduced. The proposed method i s verified using real datasets with various scales. The experimental results show that the propos ed parallel computing approach greatly improves the efficiency of GME model. Thus the GME model is applicable for the analysis on large scale exon array datasets