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Productivity-aware Design and Implementation of Distributed Tree-based Search Algorithms

Tiago Carneiro 1 Nouredine Melab 1
1 BONUS - Optimisation de grande taille et calcul large échelle
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : Parallel tree search algorithms offer viable solutions to problems in different areas, such as operations research, machine learning and artificial intelligence. This class of algorithms is highly compute-intensive, irregular and usually relies on context-specific data structures and handmade code optimizations. Therefore, C and C++ are the languages often employed, due to their low-level features and performance. In this work, we investigate the use of Chapel high-productivity language for the design and implementation of distributed tree search algorithms for solving combinatorial problems. The experimental results show that Chapel is a suitable language for this purpose, both in terms of performance and productivity. Despite the use of high-level features, the distributed tree search in Chapel is on average 16% slower and reaches up to 85% of the scalability observed for its MPI+OpenMP counterpart.
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Submitted on : Friday, May 24, 2019 - 2:53:22 PM
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  • HAL Id : hal-02139177, version 1

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Tiago Carneiro, Nouredine Melab. Productivity-aware Design and Implementation of Distributed Tree-based Search Algorithms. ICCS 2019 - International Conference on Computational Science, Jun 2019, Faro, Portugal. ⟨hal-02139177⟩

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