Search

As an emerging manufacture technology, block copolymer directed self-assembly (DSA) is promising for via layer fabrication. Meanwhile, redundant via insertion is considered as an essential step for yield improvement. For better reliability and manufacturability, in this paper, we first concurrently consider DSA guiding template cost assignment with multiple redundant via and dummy via insertion. Firstly, by analyzing the structure property of guiding templates, we propose a building-block based solution expression to discard redundant solutions. Then, honoring the compact solution expression, we construct a conflict graph with dummy via insertion, and then formulate the problem to an integer linear programming (ILP). In addition, to optimize the guiding template cost, we incorporate it into the objective of ILP by introducing vertex weight and edge weight in conflict graph. To make a good trade-off between solution quality and runtime, we relax the ILP to an unconstrained nonlinear programming (UNP). Finally, a line search optimization algorithm is proposed to solve the UNP. Experimental results verify the effectiveness of our new solution expression and the efficiency of our proposed algorithm. Specifically, our guiding template cost optimization method can save 18% total guiding template cost. • In this journal version, we first use multiple redundant via insertion technique to further improve the manufacture rate and insertion rate for the DSA guiding template and redundant via insertion problem. In Section 1, we present the role of multiple redundant via insertion by illustrating an example as Figure 4. • In this journal version, we first consider the cost of DSA guiding template. Complex templates with more holes would introduce larger overlays than regular templates with less holes. Considering guiding template cost can reduce overlays. • For the DSA guiding template assignment with multiple redundant via and dummy via insertion (DMRD) problem, we prove its NP complexity in Section 2.3. • In Section 3.2, we add the introduction of our graph reduction technique. • In Section 3.3, we add the introduction and relationship of guiding template cost, building-block cost and template edge weight. • In Section 4.3, we prove the local convergence and analyze the efficiency of our unconstrained nonlinear programming (UNP) solver. • In Section 4.4, we extend our ILP formulation in conference paper to consider guiding template cost, which is a quadratic integer programming (QIP). Furthermore, the QIP also can be solved by our UNP solver. • In Section 5, we add experimental result comparison of our ILP solver with previous works. And we add the comparison of our UNP solver and the ILP solver in TCAD'17 [18] on nine much larger benchmarks in Table 2. In addition, 1 we compare the guiding template cost between our UNP solver with guiding template cost and without guiding template cost in Section 5.3. [ABSTRACT FROM AUTHOR]

Floorplanning is a crucial step in very large scale integration design flow. It provides valuable insights into the hardware decisions and estimates a floorplan with different cost metrics. In this paper, to handle a multi-objective thermal-aware non-slicing floorplanning optimization problem efficiently, an adaptive hybrid memetic algorithm is presented to optimize the area, the total wirelength, the maximum temperature and the average temperature of a chip. In the proposed algorithm, a genetic search algorithm is used as a global search method to explore the search space as much as possible, and a modified simulated annealing search algorithm is used as a local search method to exploit information in the search region. The global exploration and local exploitation are balanced by a death probability strategy. In this strategy, according to the natural mechanisms, each individual in the population is endowed with an actual age and a dynamic survival age. Experimental results on the standard tested benchmarks show that the proposed algorithm is efficient to obtain floorplans, with decreasing the average and the peak temperature. [ABSTRACT FROM AUTHOR]