Recent Developments in Bit-Parallel Algorithms

Segundo, Pablo San; Rodríguez-Losada, D.; Rossi, Cláudio

doi:10.5772/6076

Cited by 3 publications

References 20 publications

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Productivity-Aware Design and Implementation of Distributed Tree-Based Search Algorithms

Carneiro

Melab

2019

Lecture Notes in Computer Science

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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 computeintensive, irregular and usually relies on context-specific data structures and hand-made 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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Productivity-Aware Design and Implementation of Distributed Tree-Based Search Algorithms

Carneiro

Melab

2019

Lecture Notes in Computer Science

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A GPU-Based Backtracking Algorithm for Permutation Combinatorial Problems

Pessoa

Gmys

Melab

et al. 2016

Algorithms and Architectures for Parallel Processing

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International audienceThis work presents a GPU-based backtracking algorithm for permutation combinatorial problems based on the Integer-Vector-Matrix (IVM) data structure. IVM is a data structure dedicated to permutation combinatorial optimization problems. In this algorithm, the load balancing is performed without intervention of the CPU, inside a work stealing phase invoked after each node expansion phase. The proposed work stealing approach uses a virtual n-dimensional hypercube topology and a triggering mechanism to reduce the overhead incurred by dynamic load balancing. We have implemented this new algorithm for solving instances of the Asymmetric Travelling Salesman Problem by implicit enumeration, a scenario where the cost of node evaluation is low, compared to the overall search procedure. Experimental results show that the dynamically load balanced IVM-algorithm reaches speed-ups up to 17X over a serial implementation using a bitset-data structure and up to 2X over its GPU counterpart

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