Compared to the traditional synchronous parallel computing, an asynchronous parallel alternating direction method (ADM) for total variation (TV) minimization reconstruction, namely asynchronous alternating direction total variation minimization method (Async-ADTVM), is proposed in this paper. Under the asynchronous parallel computing framework, Async-ADTVM transforms TV minimization reconstruction model to the problem of fixed-point iteration, which is solved by asynchronous parallel ADM. It is implemented on the graphics processing unit (GPU) cluster based on message passing interface technology. Experimental results show that the proposed Async-ADTVM can provide a little higher calculation accuracy than ADTVM. Meanwhile, it can provide a higher speed-up ratio than the traditional multi-GPU acceleration strategy when the performance of each GPU is different.