After the completion of human genome sequencing, the biologists require higher processing and analysis power to handle the huge gene data. Computing is a basic research method of bioinformatics, many bioinformatics programs have some common features, such as huge data volume, relative simple algorithm, few operation types, many repeating processes, showing that these programs are potentially parallelizable. When running in a general computer, these programs not only waste a lot of system resources, but also need complex maintenance. However, a lot of program still couldn't get a satisfying result within limited time. A kind of general algorithm-reconfigurable hardware accelerator architecture is presented, the principle of how to map the global Smith-Waterman algorithm to the hardware is discussed and its possible applications in other fields are pointed out.