The　Heterogeneous　Network-on-Chip　(HNoC)　integrates　CPU　cores,　Graphic　Processing　Unit　(GPU)　cores,　last-level-cache　and　memory　controllers.　The　heterogeneity　of　this　architecture　inevitably　brings　resource　contention　and　energy　shortage.　In　this　work,　we　first　study　the　impact　of　different　capacity　of　router　buffers　on　communication　delay　and　energy　consumption.　After　comprehensive　evaluation　with　a　spectrum　of　benchmarks　with　different　characteristics,　we　reveal　the　implicit　tradeoff　between　performance　and　energy　consumption　under　different　constrains　of　buffer　resource.　We　further　show　that　intelligently　allocating　more　on-chip　network　buffer　resources　to　compute-intensive　nodes　can　significantly　improve　system　performance.　We　introduce　a　runtime　strategy　that　dynamically　allocates　network　buffers　to　applications　based　on　application　characteristics.　Our　evaluation　shows　that　our　system　reduces　the　communication　delay　by　55.47%　on　average,　and　reduces　energy　consumption　of　the　system　by　21%　on　average.