A distributed implementation of Structured Gamma

Paillard, Gabriel; França, Felipe M. G.; Filho, J. Assreuy

doi:10.1109/icpads.2001.934852

Cited by 6 publications

(12 citation statements)

References 4 publications

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“…It is important to note that while exists satisfied conditions for reactions executions, such reactions will be performed and consequently will transform the multiset. Therefore, if one or more reactions conditions are satisfied for some subsets of multiset simultaneously, the decision of which reaction will execute occurs in a nondeterministic way, since these reactions may be performed independently and simultaneously, which makes the Gamma computational model a naturally parallel environment [13].…”

Section: B Gammamentioning

confidence: 99%

“…In the Gamma paradigm, this operation can be performed through a unique reaction, as depicted in Equation (2). We use the syntax of Gamma reactions based on the Gamma implementation provided by Juarez Muylaert [13].…”

Section: B Gammamentioning

confidence: 99%

“…If by list B L has no condition expression, then arithmetic nodes and the edges, connecting each input element from replace list to arithmetic operators, are created at lines 18-21. Otherwise, Steer nodes are generated with related comparison nodes and their true port are linked to the arithmetic nodes at lines [13][14][15][16]. Note that, only analyzing reaction syntax does not provide enough information to produce Inctag nodes.…”

Section: B Conversion Algorithmmentioning

confidence: 99%

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Exploring the Equivalence between Dynamic Dataflow Model and Gamma - General Abstract Model for Multiset mAnipulation

Mello

Araújo

Alves

et al. 2019

2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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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.

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Section: B Gammamentioning

confidence: 99%

Section: B Gammamentioning

confidence: 99%

Section: B Conversion Algorithmmentioning

confidence: 99%

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Exploring the Equivalence between Dynamic Dataflow Model and Gamma - General Abstract Model for Multiset mAnipulation

Mello

Araújo

Alves

et al. 2019

2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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“…The

Γ

operator can be formally defined as: 14

\begin{align} normalΓ false(false(R_{1}, A_{1} false), \dots, false(R_{m}, A_{m} false) false) false(M false) \\ = i f \forall i \in false[1, m false], \forall x_{1}, \dots, x_{n} \in M, \neg R_{i} false(x_{i}, \dots, x_{n} false) \\ t h e n M \\ e l s e l e t x_{1}, \dots, x_{n} \in M, l e t i \in false[1, m false] s u c h t h a t \\ R_{i} false(x_{1}, \dots, x_{n} false) i n \\ normalΓ false(false(R_{1}, A_{1} false), \dots, false(R_{m}, A_{m} false) false) false(false(M prefix- x_{1}, \dots, x_{n} false) \\ + A_{i} false(x_{1}, \dots, x_{n} false) false) . \end{align}

…”

Section: Introductionunclassified

“…While there exists satisfied conditions for reactions executions, such reactions will be performed and, consequently, will transform the multiset. Therefore, if one or more reaction conditions are satisfied for some subsets from a multiset simultaneously, the decision of which reaction will execute occurs in a nondeterministic way, since these reactions may be performed independently and simultaneously, which makes the Gamma computational model a naturally parallel environment 14 …”

Section: Introductionmentioning

confidence: 99%

Gamma — General Abstract Model for Multiset mAnipulation and dynamic dataflow model: An equivalence study

Mello

Araújo

Alves

et al. 2021

Concurrency and Computation

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With the increase of the search for computational models where the expression of parallelism occurs naturally, some paradigms arise as options for the current generation of computers. In this context, dynamic dataflow and Gamma—General Abstract Model for Multiset mAnipulation—emerge as interesting computational model choices. In dynamic dataflow model, operations are performed as soon as their associated operands 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 nondeterministic execution model inspired by an abstract chemical machinemetaphor, 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. 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.

show abstract