A Data-Flow Based Coordination Approach to Concurrent Software Engineering

Penczek, Frank; Wei, Cheng; Grelck, Clemens; Kirner, Raimund; Scheuermann, Bernd; Shafarenko, Alex

doi:10.1109/dfm.2012.14

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…S-Net is not at all confined to classical streaming applications as we have demonstrated through a number of numerical application case studies [28,44,45]. We have not yet implemented any of the methods for electromagnetic scattering problems described earlier in this paper, and, unfortunately, for the time being we lack the resources to do so.…”

Section: High-level Macro-dataflow Coordinationmentioning

confidence: 99%

Parallelization of Hierarchical Matrix Algorithms for Electromagnetic Scattering Problems

Larsson¹,

Zafari²,

Righero³

et al. 2019

Lecture Notes in Computer Science

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Numerical solution methods for electromagnetic scattering problems lead to large systems of equations with millions or even billions of unknown variables. The coefficient matrices are dense, leading to large computational costs and storage requirements if direct methods are used. A commonly used technique is to instead form a hierarchical representation for the parts of the matrix that corresponds to far-field interactions. The overall computational cost and storage requirements can then be reduced to O(N log N). This still corresponds to a large-scale simulation that requires parallel implementation. The hierarchical algorithms are rather complex, both regarding data dependencies and communication patterns, making parallelization non-trivial. In this chapter, we describe two classes of algorithms in some detail, we provide a survey of existing solutions, we show results for a proof-of-concept implementation, and we provide various perspectives on different aspects of the problem. The list of authors is organized into three subgroups, Larsson and Zafari (coordination and proof-of-concept implementation), Righero, Francavilla, Giordanengo, Vipiana, and Vecchi (definition of and expertise relating to the application), Kessler, Ancourt, and Grelck (perspectives and parallel expertise).

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Section: High-level Macro-dataflow Coordinationmentioning

confidence: 99%

Parallelization of Hierarchical Matrix Algorithms for Electromagnetic Scattering Problems

Larsson¹,

Zafari²,

Righero³

et al. 2019

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the compute() function the application programmer can use the data received from the linked instructions (line 16) and send the results to the output linked instructions (line 19). After that, the instructions are created (lines [21][22] and linked together (lines [23][24]. Eventually, optional parameters may be specified (line 26) and the runtime can be created and started (line 27).…”

Section: Programmability Aspectsmentioning

confidence: 99%

“…S-Net [22] is a mature dataflow model, providing static soundness guarantees and recursive graphs. Despite such features are not provided by our framework, our work is orthogonal to S-Net for two main reasons.…”

Section: Related Workmentioning

confidence: 99%

A Power-Aware, Self-Adaptive Macro Data Flow Framework

Danelutto

Sensi

Torquati

2017

Parallel Process. Lett.

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The dataflow programming model has been extensively used as an effective solution to implement efficient parallel programming frameworks. However, the amount of resources allocated to the runtime support is usually fixed once by the programmer or the runtime, and kept static during the entire execution. While there are cases where such a static choice may be appropriate, other scenarios may require to dynamically change the parallelism degree during the application execution. In this paper we propose an algorithm for multicore shared memory platforms, that dynamically selects the optimal number of cores to be used as well as their clock frequency according to either the workload pressure or to explicit user requirements. We implement the algorithm for both structured and unstructured parallel applications and we validate our proposal over three real applications, showing that it is able to save a significant amount of power, while not impairing the performance and not requiring additional effort from the application programmer.

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An Efficient Scalable Runtime System for Macro Data Flow Processing Using S-Net

Gijsbers

Grelck

2013

Int J Parallel Prog

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A Data-Flow Based Coordination Approach to Concurrent Software Engineering

Cited by 3 publications

References 24 publications

Parallelization of Hierarchical Matrix Algorithms for Electromagnetic Scattering Problems

Parallelization of Hierarchical Matrix Algorithms for Electromagnetic Scattering Problems

A Power-Aware, Self-Adaptive Macro Data Flow Framework

An Efficient Scalable Runtime System for Macro Data Flow Processing Using S-Net

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