In　the　Heterogeneous　multi-core　architecture,　CPU　and　GPU　processor　are　integrated　on　the　same　chip,　which　poses　a　new　challenge　to　the　last-level　cache　management.　In　this　architecture,　the　CPU　application　and　the　GPU　application　execute　concurrently,　accessing　the　last-level　cache.　CPU　and　GPU　have　different　memory　access　characteristics,　so　that　they　have　differences　in　the　sensitivity　of　last-level　cache　(LLC)　capacity.　For　many　CPU　applications,　a　reduced　share　of　the　LLC　could　lead　to　significant　performance　degradation.　On　the　contrary,　GPU　applications　can　tolerate　increase　in　memory　access　latency　when　there　is　sufficient　thread-level　parallelism.　Taking　into　account　the　GPU　program　memory　latency　tolerance　characteristics,　this　paper　presents　a　method　that　let　GPU　applications　can　access　to　memory　directly,　leaving　lots　of　LLC　space　for　CPU　applications,　in　improving　the　performance　of　CPU　applications　and　does　not　affect　the　performance　of　GPU　applications.　When　the　CPU　application　is　cache　sensitive,　and　the　GPU　application　is　insensitive　to　the　cache,　the　overall　performance　of　the　system　is　improved　significantly