Evolutionary Computing on Consumer Graphics Hardware

We propose implementing a parallel EA on consumer graphics cards, which we can find in many PCs. This lets more people use our parallel algorithm to solve large-scale, real-world problems such as data mining. Parallel evolutionary algorithms run on consumer-grade graphics hardware achieve better execution times than ordinary evolutionary algorithms and offer greater accessibility than those run on high-performance computers

Authors

• Ka-Ling Fok
• Tien-Tsin Wong
• Man-Leung Wong

Keywords

• Hardware
• Engines
• Computer graphics
• Rendering (computer graphics)
• Genetic programming
• Concurrent computing
• Parallel algorithms
• Toy industry
• Pipelines
• Evolutionary computation
• Population Size
• Data Mining
• Population Of Individuals
• Parallelization
• Evolutionary Algorithms
• Graphics Processing Unit
• High-performance Computing
• Evolutionary Strategy
• Graphics Card
• Parallel Algorithm
• Search Point
• Evolutionary Programming
• Random Generation
• Data Transfer
• Large Population Size
• Tournament
• Individuals In Generation
• Generations Of Evolution
• Texture Components
• Graphics Processing Unit Memory
• ubiquitous computing
• pervasive computing
• scientific computing on graphics-processing units