There　are　many　large-size　and　difficult　computational　problems　in　mathematics　and　computer　science.　For　many　of　these　problems,　traditional　computers　cannot　handle　the　mass　of　data　in　acceptable　timeframes,　which　we　call　an　NP　problem.　DNA　computing　is　a　means　of　solving　a　class　of　intractable　computational　problems　in　which　the　computing　time　grows　exponentially　with　problem　size.　This　paper　proposes　a　parallel　algorithm　model　for　the　universal　3-SAT　problem　based　on　the　Adleman-Lipton　model　and　applies　biological　operations　to　handling　the　mass　of　data　in　solution　space.　In　this　manner,　we　can　control　the　run　time　of　the　algorithm　to　be　finite　and　approximately　constant.