Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. This paper describes how fine-grained parallel genetic algorithms can be mapped to programmable graphics hardware found in commodity PCs. The approach stores chromosomes and their fitness values in texture memory on the graphics card. Both fitness evaluation and genetic operations are implemented entirely with fragment programs executed on the GPU in parallel. The paper demonstrate the effectiveness of this approach by comparing it with a compatible software implementation. The presented approach benefits from the advantages of parallel genetic algorithms on a low-cost platform. (http://www.cad.zju.edu.cn/home/yqz/)