Gaussian elimination based sparse LU factorization with partial pivoting is important to
many scientific applications, but it is still an open problem to develop a high performance
sparse LU code on distributed memory machines. The main difficulty is that partial pivoting
operations make structures of L and U factors unpredictable beforehand. This paper presents
an approach called S? for parallelizing this problem on distributed memory machines. The S?