GPUs　are　widely　used　to　accelerate　general　purpose　applications,　and　could　hide　memory　latency　through　massive　multithreading.　But　multithreading　can　increase　contention　for　the　L1　data　caches　(L1D).　This　problem　is　exacerbated　when　an　application　contains　irregular　memory　references　which　would　lead　to　un-coalesced　memory　accesses.　In　this　paper,　we　propose　a　simple　yet　effective　GPU　cache　Bypassing　scheme　for　Un-Coalesced　Loads　(BUCL).　BUCL　makes　bypassing　decisions　at　two　granularities.　At　the　instruction-　level,　when　the　number　of　memory　accesses　generated　by　a　non-coalesced　load　instruction　is　bigger　than　a　threshold,　referred　as　the　threshold　of　un-coalescing　degree　(TUCD),　all　the　accesses　generated　from　this　load　will　bypass　L1D.　The　reason　is　that　the　cache　data　filled　by　un-coalesced　loads　typically　have　low　probabilities　to　be　reused.　At　the　level　of　each　individual　memory　access,　when　the　L1D　is　stalled,　the　accessed　data　is　likely　with　low　locality,　and　the　utilization　of　the　target　memory　sub-partition　is　not　high,　this　memory　access　may　also　bypass　L1D.　Our　experiments　show　that　BUCL　achieves　36%　and　5%　performance　improvement　over　the　baseline　GPU　for　memory　un-　coalesced　and　memory　coherent　benchmarks,　respectively,　and　also　significantly　outperforms　prior　GPU　cache　bypassing　and　warp　throttling　schemes.