An Incremental Parallel PGAS-based Tree ...
Document type :
Communication dans un congrès avec actes
Title :
An Incremental Parallel PGAS-based Tree Search Algorithm
Author(s) :
Carneiro, Tiago [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Optimisation de grande taille et calcul large échelle [BONUS]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Conference title :
HPCS 2019 - International Conference on High Performance Computing & Simulation
City :
Dublin
Country :
Irlande
Start date of the conference :
2019-07-15
English keyword(s) :
Tree Search Algorithms
MPI+OpenMP
Chapel
PGAS
High-productivity Language
MPI+OpenMP
Chapel
PGAS
High-productivity Language
HAL domain(s) :
Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
English abstract : [en]
In this work, we show that the Chapel high-productivity language is suitable for the design and implementation of all aspects involved in the conception of parallel tree search algorithms for solving combinatorial problems. ...
Show more >In this work, we show that the Chapel high-productivity language is suitable for the design and implementation of all aspects involved in the conception of parallel tree search algorithms for solving combinatorial problems. Initially, it is possible to hand-optimize the data structures involved in the search process in a way equivalent to C. As a consequence, the single-threaded search in Chapel is on average only 7% slower than its counterpart written in C. Whereas programming a multicore tree search in Chapel is equivalent to C-OpenMP in terms of performance and programmability, its productivity-aware features for distributed programming stand out. It is possible to incrementally conceive a distributed tree search algorithm starting from its multicore counterpart by adding few lines of code. The distributed implementation performs load balancing among different computer nodes and also exploits all CPU cores of the system. Chapel presents an interesting trade-off between programmability and performance despite the high level of its features. The distributed tree search in Chapel is on average 16% slower and reaches up to 80% of the scalability achieved by its C-MPI+OpenMP counterpart.Show less >
Show more >In this work, we show that the Chapel high-productivity language is suitable for the design and implementation of all aspects involved in the conception of parallel tree search algorithms for solving combinatorial problems. Initially, it is possible to hand-optimize the data structures involved in the search process in a way equivalent to C. As a consequence, the single-threaded search in Chapel is on average only 7% slower than its counterpart written in C. Whereas programming a multicore tree search in Chapel is equivalent to C-OpenMP in terms of performance and programmability, its productivity-aware features for distributed programming stand out. It is possible to incrementally conceive a distributed tree search algorithm starting from its multicore counterpart by adding few lines of code. The distributed implementation performs load balancing among different computer nodes and also exploits all CPU cores of the system. Chapel presents an interesting trade-off between programmability and performance despite the high level of its features. The distributed tree search in Chapel is on average 16% slower and reaches up to 80% of the scalability achieved by its C-MPI+OpenMP counterpart.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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