Accurate　and　high-fidelity　finite　element　(FE)　models　are　in　great　demand　in　the　design,　performance　assessment,　and　life-cycle　maintenance　of　long-span　cable-stayed　bridges.　The　structural　system　of　a　long-span　cable-stayed　bridge　is　often　huge　in　size　and　complex　with　many　components　connected　and　various　materials　constituted.　Therefore,　the　FE　model　of　a　long-span　cable-stayed　bridge　involves　a　large　number　of　elements　and　nodes　with　many　uncertainties.　The　model　updating　of　the　FE　model　to　best　represent　a　real　bridge　is　necessary　but　very　challenging.　One　of　the　challenging　issues　is　that　the　numerical　computation　needed　for　searching　the　global　optimum　of　a　large　set　of　structural　parameters　is　so　extensive　that　the　existing　FE　(not　surrogate)　model-based　updating　methods　cannot　fulfill　this　task.　In　this　study,　a　cluster　computing-aided　FE　model　updating　framework　is　proposed　for　the　high-performance　FE　model　updating　of　large　and　complex　structures.　In　the　framework,　several　computer　software　packages,　including　MSC.Marc,　Python,　and　MATLAB,　are　interconnected　for　making　use　of　their　respective　functions　of　strength.　The　shake　table　test　of　a　scaled　physical　structure　of　the　Sutong　cable-stayed　bridge　in　China　is　used　to　validate　the　accuracy　and　efficiency　of　the　proposed　framework.　The　simulated　bridge　responses　based　on　the　updated　FE　model　are　in　good　agreement　with　the　measured　ones　from　the　shake　table　test.　The　successful　application　of　the　proposed　framework　provides　a　reference　for　the　model　updating　of　other　types　of　large　and　complex　structures.