Optimization Techniques on GPU: A Survey

Rashmi Sharan Sinha, Satvir Singh
SBS State Technical Campus, Ferozepur, Punjab, India
International Multi Track Conference on Science, Engineering & Technical Innovations, 2014


   title={Optimization Techniques on GPU},

   author={Sinha, Rashmi Sharan and Singh, Satvir},

   booktitle={International Multi Track Conference on Science, Engineering & Technical Innovations},

   address={CT Group of Institutions, Jalandhar},





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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 applications.
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