A new sufficient dimension reduction method based on kernel canonical functions. This new method is distribution free and highly scalable. We give theoretical proof of the sufficient dimension reduction property. We present efficient algorithms and discuss the choice of loss function. Extensive experiments demonstrate its advantage over existing approaches.