Optimization Techniques on GPU: A Survey

In this paper, we present a comprehensive survey on parallelizing computations involved in optimization problem, on GPU using CUDA. Many researchers have reported significant speedup using CUDA on GPU. Stochastic algorithms, Metaheuristic algorithms and Heuristic algorithms i.e., Mixed Integer Non-linear Programming (MINLP), Central Force Optimization (CFO), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), etc. are exploring/exploiting the processing power of GPU. GPGPU shows tremendous speedups of 6x to 7x in Steady State Genetic Algorithm to 10,000x speedups in CFO. GPU have multithread cores with high memory bandwidth which allow for greater ease of use and also more radially support a layer body of

[1]  Kalyanmoy Deb,et al.  Parallelization of binary and real-coded genetic algorithms on GPU using CUDA , 2010, IEEE Congress on Evolutionary Computation.

[2]  Ludek Žaloudek,et al.  GPU Accelerators for Evolvable Cellular Automata , 2009, 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns.

[3]  Asim Munawar,et al.  Advanced genetic algorithm to solve MINLP problems over GPU , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[4]  Mark Harman,et al.  Evolving a CUDA kernel from an nVidia template , 2010, IEEE Congress on Evolutionary Computation.

[5]  J. Kennedy,et al.  Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[6]  Fred Stentiford,et al.  An evolutionary programming approach to the simulation of visual attention , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[7]  L. Durbeck,et al.  The Cell Matrix: an architecture for nanocomputing , 2001 .

[8]  Kalyan S. Perumalla.  Discrete-event Execution Alternatives on General Purpose Graphical Processing Units (GPGPUs) , 2006, 20th Workshop on Principles of Advanced and Distributed Simulation (PADS'06).

[9]  Enrique Alba,et al.  A multi-GPU implementation of a Cellular Genetic Algorithm , 2010, IEEE Congress on Evolutionary Computation.

[10]  Mostafa Bamha,et al.  An efficient parallel algorithm for evaluating join queries on heterogeneous distributed systems , 2009, 2009 International Conference on High Performance Computing (HiPC).

[11]  Alexandr Stefek,et al.  Benchmarking of heuristic optimization methods , 2011, 14th International Conference Mechatronika.

[12]  Marco Tomassini,et al.  On the Generation of High-Quality Random Numbers by Two-Dimensional Cellular Automata , 2000, IEEE Trans. Computers.

[13]  Maurice Herlihy,et al.  Scout: High-Performance Heterogeneous Computing Made Simple , 2011, 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum.