In　this　paper,　we　propose　an　algorithm　for　a　nonsmooth　convex　optimization　problem　arising　in　very　large-scale　integrated　circuit　placement.　The　objective　function　is　the　sum　of　a　large　number　of　Half-Perimeter　Wire　Length　(HPWL)　functions　and　a　strongly　convex　function.　The　algorithm　is　based　on　Nesterov’s　smoothing　and　excessive　gap　techniques.　The　main　advantage　of　the　algorithm　is　that　it　can　capture　the　HPWL　information　in　the　process　of　optimization,　and　every　subproblem　has　an　explicit　solution　in　the　process　of　optimization.　The　convergence　rate　of　the　algorithm　is　O(1/k2),　where　k　is　the　iteration　counter,　which　is　optimal.　We　also　present　preliminary　experiments　on　nine　placement　contest　benchmarks.　Numerical　examples　confirm　the　theoretical　results.　©　2014,　Operations　Research　Society　of　China,　Periodicals　Agency　of　Shanghai　University,　and　Springer-Verlag　Berlin　Heidelberg.