This paper presents design and experimental results of a parallel linear equation solver by asynchronous partial Gauss-Seidel method. The basic idea of this method is derived from the asynchronous iterative method; newly computed values of unknowns are broadcast to all other processors and are incorporated into computing the next value immediately after they are received. However, since the asynchronous iterative method requires frequent data passing, it is difficult to achieve high performance on practical cluster computing systems due to its enormous communication overhead. To avoid it, the asynchronous partial Gauss-Seidel method reduces frequency of broadcasting new values of unknowns by passing multiple values in a chunk. The experimental results show the advantage of the asynchronous partial Gauss-Seidel method.