Genetic Programming on Graphics Processing Units ...

Genetic Programming on Graphics Processing Units Bibliography Simon Harding Memorial Univeristy, Canada www.gpgpgpu.com www.evolutioninmaterio.com [email protected] 09 February 2010

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Overview

The use of Graphics Processing Units (GPUs) in scientific computing is becoming increasingly common. GPUs are low cost parallel processors that can readily be exploited for many types of general purpose computation. Recently, the computational intelligence community has started to develop for the GPU platform. The papers listed here are primarily about the use of GPUs as a platform for Genetic Programming. However, I have also included other related papers that may be of interest to the community. This bibliography was generated by the web page www.gpgpgpu.com. Please refer to the web page for the latest version. If you have papers that should be included, or if you spot any errors, please email: [email protected].

References [1] Enrique Alba and Bernabe Dorronsoro. Springer, 2008.

Cellular genetic algorithms.

[2] Wolfgang Banzhaf and Simon Harding. Accelerating evolutionary computation with graphics processing units. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 3237–3286, New York, NY, USA, 2009. ACM.

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[3] Wolfgang Banzhaf, Simon Harding, William B. Langdon, and Garnett Wilson. Accelerating genetic programming through graphics processing units. In Genetic Programming Theory and Practice VI, pages 1–19. 2009. [4] Joseph M. Cavanagh, Thomas E. Potok, and Xiaohui Cui. Parallel latent semantic analysis using a graphics processing unit. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2505–2510, New York, NY, USA, 2009. ACM. [5] Darren M. Chitty. A data parallel approach to genetic programming using programmable graphics hardware. In Proceedings of the 9th annual conference on Genetic and evolutionary computation, pages 1566–1573, London, England, 2007. ACM. [6] Josefa D´ıaz, Francisco Fern´ andez de Vega, J. Ignacio Hidalgo, Oscar Garnica, and Sonia L´ opez. Applying genetic algorithms to resizable caches configuration for improving smt performance. In Jos´e L. Risco-Mart´ın and Oscar Garnica, editors, WPABA’09: Proceedings of the Second International Workshop on Parallel Architectures and Bioinspired Algorithms (WPABA 2009), pages 39–48, Raleigh, NC, USA, September 12-16 2009. Universidad Complutense de Madrid. [7] Ka-Ling Fok and Tien-Tsin Wong. Evolutionary computing on consumer graphics hardware. Intelligent Systems, IEEE, 22(2):69–78, 2007. [8] Stephane Gobron, Herva Bonafos, and Daniel Mestre. GPU accelerated computation and visualization of hexagonal cellular automata. In Cellular Automata, pages 512–521. 2008. [9] S. Harding and W. Banzhaf. Genetic programming on GPUs for image processing. International Journal of High Performance Systems Architecture, 1(4):231 – 240, 2008. [10] Simon Harding and Wolfgang Banzhaf. Fast genetic programming and artificial developmental systems on GPUs. In Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications, page 2. IEEE Computer Society, 2007. [11] Simon Harding and Wolfgang Banzhaf. Fast genetic programming on GPUs. In Genetic Programming, pages 90–101. 2007. [12] Simon Harding and Wolfgang Banzhaf. Distributed genetic programming on gpus using cuda. In Jos´e L. Risco-Mart´ın and Oscar Garnica, editors, WPABA’09: Proceedings of the Second International Workshop on Parallel Architectures and Bioinspired Algorithms (WPABA 2009), pages 1–10, Raleigh, NC, USA, September 12-16 2009. Universidad Complutense de Madrid.

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[13] Changhao Jiang and M. Snir. Automatic tuning matrix multiplication performance on graphics hardware. In Parallel Architectures and Compilation Techniques, 2005. PACT 2005. 14th International Conference on, pages 185–194, 2005. [14] F. Kr¨ uger, S O. Maitre, Jimenez, L. Baumes, and P. Collet. Speedups between x70 and x120 for a generic local search (memetic) algorithm on a single gpgpu chip. In EvoNum 2010, volume 6024 of LNCS, pages 501–511. Springer, 2010. [15] W. Langdon and Wolfgang Banzhaf. A SIMD interpreter for genetic programming on GPU graphics cards. In Genetic Programming, pages 73–85. 2008. [16] W. Langdon and A. Harrison. GP on SPMD parallel graphics hardware for mega bioinformatics data mining. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 12(12):1169–1183, October 2008. [17] W. B. Langdon. A CUDA SIMT interpreter for genetic programming. Technical Report TR-09-05, Department of Computer Science, King’s College London, Strand, WC2R 2LS, UK, 18 June 2009. Revised. [18] W. B. Langdon. A fast high quality pseudo random number generator for nvidia cuda. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2511–2514, New York, NY, USA, 2009. ACM. [19] W. B. Langdon. Large scale bioinformatics data mining with parallel genetic programming on graphics processing units. In Francisco Fernandez de Vega and Erick Cantu-Paz, editors, Parallel and Distributed Computational Intelligence, volume 279 of Studies in Computational Intelligence, chapter 5, pages 113–141. Springer, January 2010. [20] W. B. Langdon. A many threaded CUDA interpreter for genetic programming. In Anna I Esparcia-Alcazar, Aniko Ekart, and Sara Silva, editors, EuroGP 2010, Istanbul, 7-9 April 2010. [21] William B. Langdon. Programming graphics cards with cuda for genetic programming. Ecole d’´et´e Evolution Artificielle 2010, 14-17 June 2010. Invited talk. [22] Tony E. Lewis and George D. Magoulas. Strategies to minimise the total run time of cyclic graph based genetic programming with GPUs. In Guenther Raidl, Franz Rothlauf, Giovanni Squillero, Rolf Drechsler, et al., editors, GECCO ’09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pages 1379–1386, Montreal, 8-12 July 2009. ACM.

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[23] Jian-Ming Li, Xiao-Jing Wang, Rong-Sheng He, and Zhong-Xian Chi. An efficient fine-grained parallel genetic algorithm based on GPU-Accelerated. In Network and Parallel Computing Workshops, 2007. NPC Workshops. IFIP International Conference on, pages 855–862, 2007. [24] Zhongwen Luo and Hongzhi Liu. Cellular genetic algorithms and local search for 3-SAT problem on graphic hardware. In Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, pages 2988–2992, 2006. [25] Ogier Maitre, Laurent A. Baumes, Nicolas Lachiche, Avelino Corma, and Pierre Collet. Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA. In GECCO ’09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pages 1403– 1410, New York, NY, USA, 2009. ACM. [26] Ogier Maitre, Pierre Collet, and Nicolas Lachiche. Fast evaluation of GP trees on GPGPU by optimizing hardware scheduling. In Anna Isabel Esparcia-Alcazar, Aniko Ekart, Sara Silva, Stephen Dignum, and A. Sima Uyar, editors, Proceedings of the 13th European Conference on Genetic Programming, EuroGP 2010, volume 6021 of LNCS, pages 301–312, Istanbul, 7-9 April 2010. Springer. [27] Julian Francis Miller and Simon L. Harding. Cartesian genetic programming. In Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation, pages 2701–2726, Atlanta, GA, USA, 2008. ACM. [28] Claudia Di Napoli, Maurizio Giordano, Zsolt N´emeth, and Nicola Tonellotto. A chemical metaphor to model service selection for composition of services. In Jos´e L. Risco-Mart´ın and Oscar Garnica, editors, WPABA’09: Proceedings of the Second International Workshop on Parallel Architectures and Bioinspired Algorithms (WPABA 2009), pages 11–20, Raleigh, NC, USA, September 12-16 2009. Universidad Complutense de Madrid. [29] Carlos Perez-Miguel, Jose Miguel-Alonso, and Alexander Mendiburu. Evaluating the cell broadband engine as a platform to run estimation of distribution algorithms. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2491–2498, New York, NY, USA, 2009. ACM. [30] Riccardo Poli, W B Langdon, and Nicholas Freitag McPhee. A Field Guide to Genetic Programming. Lulu.com, March 2008. [31] Riccardo Poli, William B Langdon, Nicholas F Mcphee, and John R Koza. Genetic programming an introductory tutorial and a survey of techniques and applications. 2007. [32] Petr Posp´ıchal, Jiˇr´ı Jaroˇs, and Josef Schwarz. Parallel genetic algorithm on the cuda architecture. In Applications of Evolutionary Computation, LNCS 6024, pages 442–451. Springer Verlag, 2010. 4

[33] Petr Posp´ıchal, Josef Schwarz, and Jiˇr´ı Jaroˇs. Parallel genetic algorithm solving 0/1 knapsack problem running on the gpu. In 16th International Conference on Soft Computing MENDEL 2010, pages 64–70. Brno University of Technology, 2010. [34] Carlos P´erez-Miguel, Jos´e Miguel-Alonso, and Alexander Mendiburu. Porting estimation of distribution algorithms to the cell broadband engine. In Jos´e L. Risco-Mart´ın and Oscar Garnica, editors, WPABA’09: Proceedings of the Second International Workshop on Parallel Architectures and Bioinspired Algorithms (WPABA 2009), pages 31–38, Raleigh, NC, USA, September 12-16 2009. Universidad Complutense de Madrid. [35] John Rieffel, Frank Saunders, Shilpa Nadimpalli, Harvey Zhou, Soha Hassoun, Jason Rife, and Barry Trimmer. Evolving soft robotic locomotion in physx. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2499–2504, New York, NY, USA, 2009. ACM. [36] Jos´e L. Risco-Mart´ın, Jos´e M. Colmenar, and Rub´en Gonzalo. A parallel evolutionary algorithm to optimize dynamic memory managers in embedded systems. In Jos´e L. Risco-Mart´ın and Oscar Garnica, editors, WPABA’09: Proceedings of the Second International Workshop on Parallel Architectures and Bioinspired Algorithms (WPABA 2009), pages 21–30, Raleigh, NC, USA, September 12-16 2009. Universidad Complutense de Madrid. [37] Denis Robilliard, Virginie Marion, and Cyril Fonlupt. High performance genetic programming on GPU. In Proceedings of the 2009 workshop on Bioinspired algorithms for distributed systems, pages 85–94, Barcelona, Spain, 2009. ACM. [38] Denis Robilliard, Virginie Marion-Poty, and Cyril Fonlupt. Population parallel GP on the g80 GPU. In Genetic Programming, pages 98–109. 2008. [39] Denis Robilliard, Virginie Marion-Poty, and Cyril Fonlupt. Genetic programming on graphics processing units. Genetic Programming and Evolvable Machines, 10(4):447–471, December 2009. Special issue on parallel and distributed evolutionary algorithms, part I. [40] Shigeyoshi Tsutsui and Noriyuki Fujimoto. Solving quadratic assignment problems by genetic algorithms with gpu computation: a case study. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2523–2530, New York, NY, USA, 2009. ACM. [41] Zdenek Vasicek and Lukas Sekanina. Hardware accelerators for cartesian genetic programming. In Genetic Programming, pages 230–241. 2008.

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[42] G. Wilson and W. Banzhaf. Linear genetic programming GPGPU on microsoft’s xbox 360. In Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on, pages 378–385, 2008. [43] Garnett Wilson and Wolfgang Banzhaf. Deployment of cpu and gpu-based genetic programming on heterogeneous devices. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2531–2538, New York, NY, USA, 2009. ACM. [44] Man Wong and Tien Wong. Implementation of parallel genetic algorithms on graphics processing units. In Intelligent and Evolutionary Systems, pages 197–216. 2009. [45] Man Leung Wong. Parallel multi-objective evolutionary algorithms on graphics processing units. In GECCO ’09: Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, pages 2515–2522, New York, NY, USA, 2009. ACM. [46] Man-Leung Wong and Tien-Tsin Wong. Parallel hybrid genetic algorithms on Consumer-Level graphics hardware. In Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, pages 2973–2980, 2006. [47] Man-Leung Wong, Tien-Tsin Wong, and Ka-Ling Fok. Parallel evolutionary algorithms on graphics processing unit. In Evolutionary Computation, 2005. The 2005 IEEE Congress on, volume 3, pages 2286–2293 Vol. 3, 2005. [48] Tien-Tsin Wong and Man Wong. Parallel evolutionary algorithms on Consumer-Level graphics processing unit. In Parallel Evolutionary Computations, pages 133–155. 2006. [49] Yanyan Xu, Hui Chen, Reinhard Klette, Jiaju Liu, and Tobi Vaudrey. Belief propagation implementation using cuda on an nvidia gtx 280. In Ann E. Nicholson and Xiaodong Li, editors, Australasian Conference on Artificial Intelligence, Lecture Notes in Computer Science, pages 180–189. Springer, 2009. [50] Qizhi Yu, Chongcheng Chen, and Zhigeng Pan. Parallel genetic algorithms on programmable graphics hardware. In Advances in Natural Computation, pages 1051–1059. 2005. [51] Weihang Zhu. A study of parallel evolution strategy: pattern search on a gpu computing platform. In Lihong Xu, Erik D. Goodman, Guoliang Chen, Darrell Whitley, and Yongsheng Ding, editors, GEC Summit, pages 765–772. ACM, 2009. [52] Weihang Zhu. A study of parallel evolution strategy: pattern search on a gpu computing platform. In GEC ’09: Proceedings of the first 6

ACM/SIGEVO Summit on Genetic and Evolutionary Computation, pages 765–772, New York, NY, USA, 2009. ACM. [53] Weihang Zhu and James Curry. Multi-walk parallel pattern search approach on a GPU computing platform. In Computational Science – ICCS 2009, pages 984–993. 2009.

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