Hardware-oriented ant colony optimization

Scheuermann, Bernd; Janson, Stefan; Middendorf, Martin

doi:10.1016/j.sysarc.2006.12.002

Cited by 14 publications

(6 citation statements)

References 11 publications

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“…The most important approach that mostly follows the inadvertent parallel and multiple ant colonial approaches, were specifically and significantly dedicated by the reactionary hardware-adapted parallel approaches. This was proposed by Scheuermann et.al [13], with the designs being implemented with parallel ACO algorithms or Field Programmable Gate Arrays (FPGA). This was later developed and a new solution to the adhering problem in orienting the solutions for the parallelisation was proposed Catala et.al [14].…”

Section: Paper An Effective Parallelism Topology In Ant Colony Optimization Algorithm For Medical Image Edge …mentioning

confidence: 99%

An Effective Parallelism Topology in Ant Colony Optimization algorithm for Medical Image Edge Detection with Critical Path Methodology (PACO-CPM)

Chetan¹,

Seshadri

Lokesha

2015

Int. J. Recent Contrib. Eng. Sci. IT

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In the digital world of medical transcription involving various dimensions of processes, detecting the edge of a standard medical image for clinical research/diagnosis, telemedicine and other applicative purposes requires various efficient and effective methodologies to address the needs of the processes. Among these various meta-heuristics, as the size of the problem tends to increase along with time, the processes and their elemental techniques, proven to have been providing viable solutions appeals for reserve management and lesser computation times, with the efficiency of such algorithms and algorithmic operations to be enhanced at suitable levels of abstraction. In this paper we propose an effective topological algorithm, which inhibits the characteristic features of high performance parallel enumeration in such heterogeneous computation environments. The proposed scheduler in the defined topological algorithm takes into consideration the metrics generated by As Built Critical Path (ABCP) - A hybrid methodological process. These metrics are re-initialized and processed to address the management of resources and the realization of search space. We also propose a methodology for shared memory access by the ants to perform parallel computation and as well implement the optimization factor in detecting the edge. An in-depth analysis with respect to the Speedup factor and the Execution time metrics are analyzed for various scenarios under consideration. The differentiations are evaluated and plotted for further futuristic analysis

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Section: Paper An Effective Parallelism Topology In Ant Colony Optimization Algorithm For Medical Image Edge …mentioning

confidence: 99%

An Effective Parallelism Topology in Ant Colony Optimization algorithm for Medical Image Edge Detection with Critical Path Methodology (PACO-CPM)

Chetan¹,

Seshadri

Lokesha

2015

Int. J. Recent Contrib. Eng. Sci. IT

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“…They conduct experiments on random instances of the Single Machine Total Tardiness Problem (SMTTP) with number of jobs ranging from 40 to 320 and report moderate speedups between 1.6 and 10 relative to a software implementation. Scheuermann et al continue their work on ACO for FGPAs in [80], where they propose a new ACO variant called Counter-based ACO. The algorithm is designed such that it can easily be mapped to FPGAs.…”

Section: Early Work On Non-gpu Related Acceleratorsmentioning

confidence: 99%

GPU computing in discrete optimization. Part II: Survey focused on routing problems

Schulz

Hasle

Brodtkorb

et al. 2013

EURO Journal on Transportation and Logistics

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In many cases there is still a large gap between the performance of current optimization technology and the requirements of real world applications. As in the past, performance will improve through a combination of more powerful solution methods and a general performance increase of computers. These factors are not independent. Due to physical limits, hardware development no longer results in higher speed for sequential algorithms, but rather in increased parallelism. Modern commodity PCs include a multi-core CPU and at least one GPU, providing a low cost, easily accessible heterogeneous environment for high performance computing. New solution methods that combine task parallelization and stream processing are needed to fully exploit modern computer architectures and profit from future hardware developments. This paper is the second in a series of two. Part I gives a tutorial style introduction to modern PC architectures and GPU programming. Part II gives a broad survey of the literature on parallel computing in discrete optimization targeted at modern PCs, with special focus on routing problems. We assume that the reader is familiar with GPU programming, and refer the interested reader to Part I. We conclude with lessons learnt, directions for future research, and prospects.

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“…Scheuermann et al [21,22] designed parallel implementations of ACO on Field Programmable Gate Arrays (FPGA). Considerable changes to the algorithmic structure of the metaheuristic were needed to take benefit of this particular architecture.…”

Section: Hardware-oriented Parallel Acomentioning

confidence: 99%

Parallel Ant Colony Optimization: Algorithmic Models and Hardware Implementations

Delisle¹

2013

Ant Colony Optimization - Techniques and Applications

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Hardware-oriented ant colony optimization

Cited by 14 publications

References 11 publications

An Effective Parallelism Topology in Ant Colony Optimization algorithm for Medical Image Edge Detection with Critical Path Methodology (PACO-CPM)

An Effective Parallelism Topology in Ant Colony Optimization algorithm for Medical Image Edge Detection with Critical Path Methodology (PACO-CPM)

GPU computing in discrete optimization. Part II: Survey focused on routing problems

Parallel Ant Colony Optimization: Algorithmic Models and Hardware Implementations

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