In　network　function　virtualization　(NFV),　network　functions　(NFs)　are　chained　as　a　service　function　chain　(SFC)　to　enhance　NF　management　with　low　cost　and　high　flexibility.　Recent　NFV　solutions　indicate　that　the　packet　processing　performance　of　SFCs　can　be　significantly　improved　by　offloading　NFs　to　programmable　switches.　However,　such　offloading　requires　a　deep　understanding　of　heterogeneous　NF　properties　(e.g.,　NF　resource　consumption　and　NF　performance　behaviors)　to　achieve　the　maximum　SFC　performance.　Unfortunately,　none　of　existing　solutions　provide　automatic　analysis　of　these　NF　properties.　Thus,　network　administrators　have　to　manually　examine　the　source　codes　of　NFs　and　profile　various　NF　properties　by　hand,　which　is　extremely　time-consuming　and　laborious.　In　this　article,　we　propose　LightNF,　a　novel　system　that　simplifies　NF　offloading　in　programmable　networks.　LightNF　automatically　dissects　comprehensive　NF　properties　by　means　of　code　analysis　and　performance　profiling　while　eliminating　manual　efforts.　It　then　leverages　its　analysis　results　of　NF　properties　in　its　SFC　placement　so　as　to　make　the　performance-optimal　offloading　decisions.　We　have　implemented　LightNF　on　Tofino-based　hardware　programmable　switches.　We　perform　extensive　experiments　to　evaluate　LightNF　with　a　real-world　testbed　and　large-scale　simulation.　Our　experiments　show　that　LightNF　outperforms　existing　solutions　with　an　orders-of-magnitude　reduction　in　per-packet　processing　latency　and　9.5×　improvement　in　SFC　throughput.　©　2022　IEEE.