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Exploring the Equivalence between Dynamic Dataflow Model and Gamma - General Abstract Model for Multiset mAnipulation
With the increase of the search for computational models where the expression
of parallelism occurs naturally, some paradigms arise as options for the next
generation of computers. In this context, dynamic Dataflow and Gamma - General
Abstract Model for Multiset mAnipulation) - emerge as interesting computational
models choices. In the dynamic Dataflow model, operations are performed as soon
as their associated operators are available, without rely on a Program Counter
to dictate the execution order of instructions. The Gamma paradigm is based on
a parallel multiset rewriting scheme. It provides a non-deterministic execution
model inspired by an abstract chemical machine metaphor, where operations are
formulated as reactions that occur freely among matching elements belonging to
the multiset. In this work, equivalence relations between the dynamic Dataflow
and Gamma paradigms are exposed and explored, while methods to convert from
Dataflow to Gamma paradigm and vice versa are provided. It is shown that
vertices and edges of a dynamic Dataflow graph can correspond, respectively, to
reactions and multiset elements in the Gamma paradigm. Implementation aspects
of execution environments that could be mutually beneficial to both models are
also discussed. This work provides the scientific community with the
possibility of taking profit of both parallel programming models, contributing
with a versatility component to researchers and developers. Finally, it is
important to state that, to the best of our knowledge, the similarity relations
between both dynamic Dataflow and Gamma models presented here have not been
reported in any previous work.Comment: Study submitted to the IPDPS 2019 - IEEE International Parallel and
Distributed Processing Symposiu