Productive composition of extreme-scale applications using implicitly parallel dataflow

In every decade since the 1970’s, computer scientists have re-examined dataflow-based execution models, hoping the programming productivity benefits these models promise can be realized on practical hardware platforms to implement useful applications. Based on the recent Swift/T implementation of “implicitly parallel functional dataflow” (IPFD) for extremescale systems, we believe that the dataflow model can now provide significant software productivity benefits for developing the upper levels of petascale and exascale applications. We believe dataflow models can also yield significant secondary benefits in verifiability, reliability, and energy savings – areas that are closely related to overall systems development productivity at extreme scale. We discuss here the opportunities for software productivity at these scaled presented by the use of IPFD, and the research and development efforts needed to realize these benefits.