Design and implementation of a massively parallel version of DIRECT. This paper describes several massively parallel implementations for a global search algorithm DIRECT. Two parallel schemes take different approaches to address DIRECT’s design challenges imposed by memory requirements and data dependency. Three design aspects in topology, data structures, and task allocation are compared in detail. The goal is to analytically investigate the strengths and weaknesses of these parallel schemes, identify several key sources of inefficiency, and experimentally evaluate a number of improvements in the latest parallel DIRECT implementation. The performance studies demonstrate improved data structure efficiency and load balancing on a 2200 processor cluster.

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  1. Easterling, David R.; Watson, Layne T.; Madigan, Michael L.; Castle, Brent S.; Trosset, Michael W.: Parallel deterministic and stochastic global minimization of functions with very many minima (2014)
  2. Liu, Qunfeng; Cheng, Wanyou: A modified DIRECT algorithm with bilevel partition (2014)
  3. Kvasov, Dmitri E.; Sergeyev, Yaroslav D.: Lipschitz gradients for global optimization in a one-point-based partitioning scheme (2012)
  4. di Serafino, D.; Liuzzi, G.; Piccialli, V.; Riccio, F.; Toraldo, G.: A modified DIviding RECTangles algorithm for a problem in astrophysics (2011)
  5. Gray, G.A.; Fowler, K.R.: The effectiveness of derivative-free hybrid methods for black-box optimisation (2011)
  6. Hemker, Thomas; Werner, Christian: DIRECT using local search on surrogates (2011)
  7. Griffin, Joshua D.; Kolda, Tamara G.: Asynchronous parallel hybrid optimization combining DIRECT and GSS (2010)
  8. Liuzzi, Giampaolo; Lucidi, Stefano; Piccialli, Veronica: A partition-based global optimization algorithm (2010)
  9. Liuzzi, G.; Lucidi, S.; Piccialli, V.: A DIRECT-based approach exploiting local minimizations for the solution of large-scale global optimization problems (2010)
  10. Bartholomew-Biggs, M.C.; Kane, S.J.: A global optimization problem in portfolio selection (2009)
  11. Deng, Geng; Ferris, Michael C.: Variable-number sample-path optimization (2009)
  12. Egea, Jose A.; Vazquez, Emmanuel; Banga, Julio R.; Martí, Rafael: Improved scatter search for the global optimization of computationally expensive dynamic models (2009)
  13. Kvasov, Dmitri E.; Sergeyev, Yaroslav D.: A univariate global search working with a set of Lipschitz constants for the first derivative (2009)
  14. Lamberger, Mario; Nad, Tomislav; Rijmen, Vincent: Numerical solvers and cryptanalysis (2009)
  15. Price, C.J.; Robertson, B.L.; Reale, M.: A hybrid Hooke and Jeeves -- direct method for non-smooth optimization (2009)
  16. Chiter, Lakhdar: New interpretation of the DIRECT algorithm (2008)
  17. He, Jian; Verstak, Alex; Watson, Layne T.; Sosonkina, Masha: Design and implementation of a massively parallel version of DIRECT (2008)
  18. Kvasov, Dmitri E.: Multidimensional Lipschitz global optimization based on efficient diagonal partitions (2008)
  19. Morgans, Rick C.; Zander, Anthony C.; Hansen, Colin H.; Murphy, David J.: EGO shape optimization of Horn-loaded loudspeakers (2008)
  20. Panning, Thomas D.; Watson, Layne T.; Allen, Nicholas A.; Chen, Katherine C.; Shaffer, Clifford A.; Tyson, John J.: Deterministic parallel global parameter estimation for a model of the budding yeast cell cycle (2008)

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