SP-ant: An ant colony optimization based operator scheduler for high performance distributed stream processing on heterogeneous clusters

2022 ◽  
Vol 191 ◽  
pp. 116322
Author(s):  
Mohammadreza Farrokh ◽  
Hamid Hadian ◽  
Mohsen Sharifi ◽  
Ali Jafari
Keyword(s):  
Ant Colony Optimization ◽  
High Performance ◽  
Stream Processing ◽  
Ant Colony ◽  
Heterogeneous Clusters ◽  
Distributed Stream Processing

scholarly journals High-Level Parallel Ant Colony Optimization with Algorithmic Skeletons

2021 ◽  
Author(s):  
Breno A. de Melo Menezes ◽  
Nina Herrmann ◽  
Herbert Kuchen ◽  
Fernando Buarque de Lima Neto
Keyword(s):  
Ant Colony Optimization ◽  
High Performance ◽  
Optimization Problems ◽  
Programming Model ◽  
Parallel Implementation ◽  
Ant Colony ◽  
Algorithmic Skeletons ◽  
Low Level ◽  
Programming Patterns ◽  
High Level

AbstractParallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten the execution time when solving complex optimization problems. When aiming for a GPU environment, developing efficient parallel versions of such algorithms using CUDA can be a difficult and error-prone task even for experienced programmers. To overcome this issue, the parallel programming model of Algorithmic Skeletons simplifies parallel programs by abstracting from low-level features. This is realized by defining common programming patterns (e.g. map, fold and zip) that later on will be converted to efficient parallel code. In this paper, we show how algorithmic skeletons formulated in the domain specific language Musket can cope with the development of a parallel implementation of ACO and how that compares to a low-level implementation. Our experimental results show that Musket suits the development of ACO. Besides making it easier for the programmer to deal with the parallelization aspects, Musket generates high performance code with similar execution times when compared to low-level implementations.

Adapting Ant Colony for Topology Optimization of Compliant Mechanisms With Variable Material Density

2017 ◽  
Author(s):  
Nadim Diab
Keyword(s):  
Topology Optimization ◽  
Ant Colony Optimization ◽  
High Performance ◽  
Compliant Mechanisms ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Ant Colony ◽  
Intensity Level ◽  
Material Density ◽  
Swarm Intelligence Optimization

Swarm intelligence optimization techniques are widely used in topology optimization of compliant mechanisms. The Ant Colony Optimization has been implemented in various forms to account for material density distribution inside a design domain. In this paper, the Ant Colony Optimization technique is applied in a unique manner to make it feasible to optimize for the beam elements’ cross-section and material density simultaneously. The optimum material distribution algorithm is governed by two various techniques. The first technique treats the material density as an independent design variable while the second technique correlates the material density with the pheromone intensity level. Both algorithms are tested for a micro displacement amplifier and the resulting optimized topologies are benchmarked against reported literature. The proposed techniques culminated in high performance and effective designs that surpass those presented in previous work.

scholarly journals Dynamic load balancing on heterogeneous clusters for parallel ant colony optimization

2016 ◽  
Vol 19 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Antonio Llanes ◽  
José M. Cecilia ◽  
Antonia Sánchez ◽  
José M. García ◽  
Martyn Amos ◽  
...  
Keyword(s):  
Load Balancing ◽  
Ant Colony Optimization ◽  
Dynamic Load ◽  
Ant Colony ◽  
Dynamic Load Balancing ◽  
Heterogeneous Clusters

Advanced Strategy for Droplet Routing in Digital Microfluidic Biochips Using ACO

2015 ◽  
pp. 252-284 ◽  
Author(s):  
Indrajit Pan ◽  
Tuhina Samanta
Keyword(s):  
Ant Colony Optimization ◽  
High Performance ◽  
Ant Colony ◽  
Second Phase ◽  
Phase 2 ◽  
Bounding Box ◽  
Ant Systems ◽  
Two Phases ◽  
Comparative Results ◽  
Digital Microfluidic

Significant researches are going on for high performance droplet routing in Digital Microfluidic Biochip (DMFB). This chapter elaborates an ant colony optimization based droplet routing technique for high performance design in DMFB. The method is divided into two phases. (1) In the first phase, two dedicated ants generated from each source of the droplets traverse the rectilinear path between the source-target pairs and deposit pheromone to construct rectangular bounding box. Initial bounding box helps in restricted ant movements in the next phase. (2) In the second phase, real routing path is generated. Detour and stalling phenomena are incurred to resolve routing conflict. The method has explored both single ant and multiple ant systems to address detours from the conflicting zone in search for the best possible route towards destination. The method has been simulated on several existing benchmarks and comparative results are quite encouraging.

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