  The role of scalable high-performance workflows and flexible workflow
management systems that can support multiple simulations will continue to
increase in importance. For example, with the end of Dennard scaling, there is
a need to substitute a single long running simulation with multiple repeats of
shorter simulations, or concurrent replicas. Further, many scientific problems
involve ensembles of simulations in order to solve a higher-level problem or
produce statistically meaningful results. However most supercomputing software
development and performance enhancements have focused on optimizing single-
simulation performance. On the other hand, there is a strong inconsistency in
the definition and practice of workflows and workflow management systems. This
inconsistency often centers around the difference between several different
types of workflows, including modeling and simulation, grid, uncertainty
quantification, and purely conceptual workflows. This work explores this
phenomenon by examining the different types of workflows and workflow
management systems, reviewing the perspective of a large supercomputing
facility, examining the common features and problems of workflow management
systems, and finally presenting a proposed solution based on the concept of
common building blocks. The implications of the continuing proliferation of
workflow management systems and the lack of interoperability between these
systems are discussed from a practical perspective. In doing so, we have begun
an investigation of the design and implementation of open workflow systems for
supercomputers based upon common components.
