  A distributed-memory parallelization strategy for the density matrix
renormalization group is proposed for cases where correlation functions are
required. This new strategy has substantial improvements with respect to
previous works. A scalability analysis shows an overall serial fraction of 9.4%
and an efficiency of around 60% considering up to eight nodes. Sources of
possible parallel slowdown are pointed out and solutions to circumvent these
issues are brought forward in order to achieve a better performance.
