Analytical Layer Planning for Nanometer VLSI Designs

In this thesis, we proposed an intermediate sub-process between placement and routing stage in physical design. The algorithm is for generating layer guidance for post-placement optimization technique especially buffer insertion. This issue becomes critical in nowadays VLSI chip design due to the factor of timing, congestion, and increasingly non-uniform parasitic among different metal layers. Besides, as a step before routing, this layer planning algorithm accounts for routability by considering minimized overlap area between different nets. Moreover, layer directive information which is a crucial concern in industrial design is also considered in the algorithm. The core problem is formulated as nonlinear programming problem which is composed of objective function and constraints. The problem is further solved by conjugate gradient method. The whole algorithm is implemented by C++ under Linux operating system and tested on ISPD2008 Global Routing Contest Benchmarks. The experiment results are shown in the end of this thesis and confirm the effectiveness of our approach especially in routability aspect

Analytical Layer Planning for Nanometer VLSI Designs

In this thesis, we proposed an intermediate sub-process between placement and routing stage in physical design. The algorithm is for generating layer guidance for post-placement optimization technique especially buffer insertion. This issue becomes critical in nowadays VLSI chip design due to the factor of timing, congestion, and increasingly non-uniform parasitic among different metal layers. Besides, as a step before routing, this layer planning algorithm accounts for routability by considering minimized overlap area between different nets. Moreover, layer directive information which is a crucial concern in industrial design is also considered in the algorithm. The core problem is formulated as nonlinear programming problem which is composed of objective function and constraints. The problem is further solved by conjugate gradient method. The whole algorithm is implemented by C++ under Linux operating system and tested on ISPD2008 Global Routing Contest Benchmarks. The experiment results are shown in the end of this thesis and confirm the effectiveness of our approach especially in routability aspect

A high-quality mixed-size analytical placer considering preplaced blocks and density constraints

In addition to wirelength, modern placers need to consider various constraints such as preplaced blocks and density. We propose a high-quality analytical placement algorithm considering wirelength, preplaced blocks, and density based on the log-sum-exp wirelength model proposed by Naylor et al. [20] and the multilevel framework. To handle preplaced blocks, we use a two-stage smoothing technique, Gaussian smoothing followed by level smoothing, to facilitate block spreading during global placement. The density is controlled by white-space re-allocation using partitioning and cut-line shifting during global placement and cell sliding during detailed placement. We further use the conjugate gradient method with dynamic step-size control to speed up the global placement and macro shifting to find better macro positions. Experimental results show that our placer obtains the best published results. 1

Floorplan-guided placement for large-scale mixed-size designs

In the nanometer scale era, placement has become an extremely challenging stage in modern Very-Large-Scale Integration (VLSI) designs. Millions of objects need to be placed legally within a chip region, while both the interconnection and object distribution have to be optimized simultaneously. Due to the extensive use of Intellectual Property (IP) and embedded memory blocks, a design usually contains tens or even hundreds of big macros. A design with big movable macros and numerous standard cells is known as mixed-size design. Due to the big size difference between big macros and standard cells, the placement of mixed-size designs is much more difficult than the standard-cell placement. This work presents an efficient and high-quality placement tool to handle modern large-scale mixed-size designs. This tool is developed based on a new placement algorithm flow. The main idea is to use the fixed-outline floorplanning algorithm to guide the state-of-the-art analytical placer. This new flow consists of four steps: 1) The objects in the original netlist are clustered into blocks; 2) Floorplanning is performed on the blocks; 3) The blocks are shifted within the chip region to further optimize the wirelength; 4) With big macro locations fixed, incremental placement is applied to place the remaining objects. Several key techniques are proposed to be used in the first two steps. These techniques are mainly focused on the following two aspects: 1) Hypergraph clustering algorithm that can cut down the original problem size without loss of placement Quality of Results (QoR); 2) Fixed-outline floorplanning algorithm that can provide a good guidance to the analytical placer at the global level. The effectiveness of each key technique is demonstrated by promising experimental results compared with the state-of-the-art algorithms. Moreover, using the industrial mixed-size designs, the new placement tool shows better performance than other existing approaches