Vectorization strategies for ant colony optimization on intel architectures
V Montesinos, JM García - Parallel Computing is Everywhere, 2018 - ebooks.iospress.nl
Parallel Computing is Everywhere, 2018•ebooks.iospress.nl
This paper presents an efficient parallel and vectorized implementation of three different
selection functions (Roulette Wheel, I-Roulette and DS-Roulette) for tour construction (the
most time-consuming part of the Ant Colony Optimization bio-inspired metaheuristic)
targeting two Intel multi-core processors and the Knights Corner Intel Xeon Phi coprocessor.
The results show that our best implementation (with I-Roulette as selection function) on
Xeon Phi 7120P runs up to 78.98 x faster compared to its sequential counterpart on a Xeon …
selection functions (Roulette Wheel, I-Roulette and DS-Roulette) for tour construction (the
most time-consuming part of the Ant Colony Optimization bio-inspired metaheuristic)
targeting two Intel multi-core processors and the Knights Corner Intel Xeon Phi coprocessor.
The results show that our best implementation (with I-Roulette as selection function) on
Xeon Phi 7120P runs up to 78.98 x faster compared to its sequential counterpart on a Xeon …
Abstract
This paper presents an efficient parallel and vectorized implementation of three different selection functions (Roulette Wheel, I-Roulette and DS-Roulette) for tour construction (the most time-consuming part of the Ant Colony Optimization bio-inspired metaheuristic) targeting two Intel multi-core processors and the Knights Corner Intel Xeon Phi coprocessor. The results show that our best implementation (with I-Roulette as selection function) on Xeon Phi 7120P runs up to 78.98 x faster compared to its sequential counterpart on a Xeon v2 CPU.
ebooks.iospress.nl
Showing the best result for this search. See all results