Darwin: a clusterable optimization framework
Abstract
This article introduces Darwin, a meta-heuristics based optimization tool. It has implemented various optimization algorithms: genetic algorithm,particle swarm and differential evolution. It also has two backends for execution, the first one focused on the use of a cluster and the second one on the use of local computational resources. The x86 Sniper architecture simulator was used together with the Parsec benchmark, optimizing cache parameters, to validate the developed tool. At last, it is evaluated that the tool allows the optimization using the algorithms in a simplified and parallelable way.
Keywords:
metaheuristics, cluster, optimization
References
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Eberhart, R. C., Shi, Y., and Kennedy, J. (2001). Swarm intelligence. Elsevier.
Goldberg, D. E. (1989).Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1st edition.
Li, S., Ahn, J. H., Strong, R. D., Brockman, J. B., Tullsen, D. M., and Jouppi, N. P. (2009). Mcpat: an integrated power, area, and timing modeling framework for multicore and manycore architectures. In Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture, pages 469–480. ACM.
Papa, J. P., Rosa, G. H., Rodrigues, D., and Yang, X. (2017). Libopt: An open-source platform for fast prototyping soft optimization techniques. CoRR, abs/1704.05174.
Rossell, L. B. I. (2004–2019). ts - task spooler. a simple unix batch system. https://launchpad.net/ubuntu/+source/task-spooler/0.7.5-1.
Storn, R. and Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4):341–359.
Thain, D., Tannenbaum, T., and Livny, M. (2005). Distributed computing in practice: the condor experience. Concurrency and computation: practice and experience, 17(2-4):323–356.
Published
2020-08-19
How to Cite
RUSA, Henrique A.; KRUGER, Kleber; AZEVEDO, Rodolfo.
Darwin: a clusterable optimization framework. In: REGIONAL SCHOOL OF HIGH PERFORMANCE COMPUTING FROM SÃO PAULO (ERAD-SP), 11. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 106-109.
DOI: https://doi.org/10.5753/eradsp.2020.16898.
