Abstract: Heterogeneous computing has been a trend of high-productivity computing. Matching between parallel task and architecture in heterogeneous computing becomes a key idea to realize high productivity. We provided parallel task clustering policy based on matching between parallel task and architecture. Firstly we gave the concept of high-produc- tivity and the problem of clustering on heterogeneous computing. Secondly after theoretically analyzing the relation be- tween heterogeneous matching and productivity, we gave the method of realizing respectively computing and structure matching. hhirdly we gave accordingly the architecturcaware parallel task clustering algorithm. Finally the simulation experimental results show that such algorithms can effectively realize heterogeneous matching and enhance the hetero- gcncous computing productivity.

Key words: Heterogeneous computing, Parallel task matching, Architecturcaware, Clustering