Shrinkage of VLSI feature size and use of advanced Reticle Enhancement Technologies (RET) in manufacturing such as OPC and PSM have dramatically pushed up cost of mask. For example of a 130nm or 90nm mask set, the mask cost can easily reach one or two million US dollars. Shuttle mask is an effective method to share the mask cost by putting different chips on the same mask. Shuttle mask floorplanning is a key step to pack these chips according to certain objectives and constraints related to cost, yield, and manufacturability. In this paper, we present a simulated annealing based floorplanner to solve the shuttle mask floorplanning problem with multiple optimization objectives and constraints. We will consider area minimization, density optimization (for manufacturability enhancement with CMP), wafer utilization maximization, die-to-die inspection constraint, die orientation constraint and their combinations. A nice property of our floorplanner is that it can be easily adapted to different cost models of mask and wafer manufacturing. Experiments on industry data show promising results.
As the clock frequencies used in industrial applications increase, the timing requirements imposed on routing problems become tighter. So, it becomes important to route the nets within tight minimum and maximum length bounds. Although the problem of routing nets to satisfy maximum length constraints is a well-studied problem, there exists no sophisticated algorithm in the literature that ensures that minimum length constraints are also satisfied. In this paper, we propose a novel algorithm that effectively incorporates the min-max length constraints into the routing problem. Our approach is to use a Lagrangian relaxation framework to allocate extra routing resources around nets simultaneously during routing them. We also propose a graph model that ensures that all the allocated routing resources can be used effectively for extending lengths. Our routing algorithm automatically prioritizes resource allocation for shorter nets, and length minimization for longer nets so that all nets can satisfy their min-max length constraints. Our experiments demonstrate that this algorithm is effective even in the cases where length constraints are tight, and the layout is dense.
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