With　the　continuous　increase　in　the　speed　and　quantity　of　network　traffic,　higher　performance　requirements　are　put　forward　for　the　NFV　system.　Traditional　virtualization　technology　is　limited　by　slowing　down　of　increase　in　CPU　performance.　There　has　some　research　on　the　use　of　hardware　to　accelerate　network　functions.　However,　existing　method　only　consider　use　one　hardware　for　acceleration,　but　hardware　itself　has　limitation.　It　is　difficult　to　match　the　network　functions　and　hardware　characteristics　by　considering　the　combination　of　each　hardware　and　CPU　discretely.　In　this　paper,　we　propose　a　resource　allocation　model　of　network　function　virtualization(NFV)　based　on　heterogeneous　computing,　which　can　maximize　the　resource　utilization　and　obtain　the　global　optimal　solution.　Our　experiments　prove　that　the　genetic　algorithm　solution　method　we　propose　can　take　into　account　both　the　solution　accuracy　and　the　solution　speed,　and　obtain　an　accurate　Pareto　curve　under　the　multi-objectives　optimization　model.　©　2023　IEEE.