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17th Annual International Symposium on Parallel and distributed Computing (ISPDC)

作者： Smyk, Adam Tudruj, Marek Grochal, Lukasz Tudruj, Marek Polish Japanese Acad Informat Technol Warsaw Poland Polish Acad Scs Inst Comp Sci Warsaw Poland

ISBN: (纸本)9781538653302

The paper presents how an advanced graph partitioning optimization method was implemented inside a novel distributed program design framework PEGASUS DA which provides system support for automatic global application states monitoring. In PEGASUS DA, execution control design of distributed applications is system-supported by program global state monitoring run-time. This support provides an automatic construction of user-defined relevant strongly consistent global application states, computing global control predicates on the constructed states, evaluation of these predicates and sending asynchronous control signals to application threads and processes to stimulate the desired global state-driven reactions. The presented graph partitioning optimization algorithm is based on user-defined mixed partitioning strategies. It includes a combined use of different graph partitioning methods and different criteria for definition and assessment of produced partitions. It runs on top of basic graph partitioning methods available inside the METIS partitioning tool. The partitioning is executed by distributed processes and threads controlled by global states monitoring provided by the PEGASUS DA framework. Its use allows easy design and testing of different graph optimization strategies, finding graph partitioning optimal methods and algorithm parameters. The graph partitioning methods presented in the paper are illustrated by experiments performed with partitioning of a number of benchmark graphs to show partitioning quality (from 5% to 30% of the improvement has been observed) and execution time assessment of the proposed approach.

关键词： distributed program design tools global application states monitoring hierarchical graph/mesh partitionig

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Genetic Algorithms Execution Control Under a Global Application State Monitoring Infrastructure

Genetic Algorithms Execution Control Under a Global Applicat...

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10th International Conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Smyk, Adam Tudruj, Marek Polish Japanese Inst Informat Technol PL-02008 Warsaw Poland

ISBN: (纸本)9783642552243

In the paper a new approach to the design of parallel genetic algorithms for execution in distributed systems with multicore processors is presented. The use of a distributed genetic algorithm based on new control implementation principles is proposed for an optimized irregular computational mesh partitioning for the FDTD (Finite-Diffierence Time-Domain) problem. The algorithm defines computational mesh partitions based on two objectives: load balancing and "min-cut" - the minimal number of edges between partition elements. The control in the parallel genetic algorithm assumes the use of program execution global control functions based on global application states monitoring. A control design infrastructure is provided to a programmer based on generalized synchronization/control processes called synchronizers. They collect local states of program computational elements, compute global control predicates and send back control signals. The paper describes how the assumed infrastructure can be used for convenient global program execution control at thread and process levels applied in the proposed genetic algorithm.

关键词： distributed program design paradigms Global application states monitoring distributed program design tools Mesh partitioning Tiling FDTD

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distributed Application Global States Monitoring in PEGASUS DA Applied to Parallel Graph Partitioning

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2021年第11期33卷 e6052-e6052页

作者： Smyk, Adam Tudruj, Marek Polish Japanese Acad Informat Technol 86 Koszykowa St PL-02008 Warsaw Poland Polish Acad Sci Inst Comp Sci Warsaw Poland

This paper presents how parallel advanced graph partitioning algorithms can be designed and improved with the use of global application states monitoring of distributed programs. The proposed algorithms have been implemented inside a novel distributed program design framework program Execution Governed by Asynchronous Supervision of States in distributed Applications (PEGASUS DA). This framework provides system support for the design of execution control in distributed applications based on automated global state monitoring. Two strategies for the control design of advanced parallel/distributed graph partitioning algorithms are presented and discussed. In the first one, the parallel algorithm control runs on top of the popular graph partitioning METIS tool. The second control strategy is based on genetic programming so that partitioning primitives and the overall algorithmic control can be freely designed by the user. Advanced partitioning methods have been conveniently embedded inside the global state monitoring driven PEGASUS DA framework which controls partitioning distributed actions at the level of processes and threads. The use of the framework allowed easy design and testing of different graph optimization strategies. The presented graph partitioning methods are illustrated by experiments with benchmark graphs. The experiments have comparatively assessed the obtained graph partitioning quality (visible improvement has been observed) and have identified benefits of the proposed approach for programmers.

关键词： application global states monitoring distributed program design tools parallel graph partitioning

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