  A parallel direct solution approach based on domain decomposition method
(DDM) and directed acyclic graph (DAG) scheduling is outlined. Computations are
represented as a sequence of small tasks that operate on domains of DDM or
dense matrix blocks of a reduced matrix. These tasks can be statically
scheduled for parallel execution using their DAG dependencies and weights that
depend on estimates of computation and communication costs. Performance
comparison with MUMPS 5.1.2 on electrically large problems suggest up to 20%
better parallel efficiency, 30% less memory and slightly faster in run-time,
while maintaining the same accuracy.
