Nowadays,　high-bandwidth　networks　are　more　easily　accessible　than　ever　before.　However,　existing　distributed　graph-processing　frameworks,　such　as　GPS,　fail　to　efficiently　utilize　the　additional　bandwidth　capacity　in　these　networks　for　higher　performance,　due　to　their　inefficient　computation　and　communication　models,　leading　to　very　long　waiting　times　experienced　by　users　for　the　graph-computing　results.　The　root　cause　lies　in　the　fact　that　the　computation　and　communication　models　of　these　frameworks　generate,　send　and　receive　messages　so　slowly　that　only　a　small　fraction　of　the　available　network　bandwidth　is　utilized.　In　this　paper,　we　propose　a　high-performance　distributed　graph-processing　framework,　called　BlitzG,　to　address　this　problem.　This　framework　fully　exploits　the　available　network　bandwidth　capacity　for　fast　graph　processing.　Our　approach　aims　at　significant　reduction　in　(i)　the　computation　workload　of　each　vertex　for　fast　message　generation　by　using　a　new　slimmed-down　vertex-centric　computation　model　and　(ii)　the　average　message　overhead　for　fast　message　delivery　by　designing　a　light-weight　message-centric　communication　model.　Evaluation　on　a　40Gbps　Ethernet,　driven　by　real-world　graph　datasets,　shows　that　BlitzG　outperforms　GPS　by　up　to　27x　with　an　average　of　20.7x.