Simultaneous block and I/O buffer floorplanning for flip-chip design

The flip-chip package gives the highest chip density of any packaging method to support the pad-limited ASIC design. One of the most important characteristics of flip-chip designs is that the input/output buffers could be placed anywhere inside a chip. In this paper, we first introduce the floorplanning problem for the flip-chip design and formulate it as assigning the positions of input/output buffers and first-stage/last-stage blocks so that the path length between blocks and bump balls as well as the delay skew of the paths are simultaneously minimized. We then present a hierarchical method to solve the problem. We first cluster a block and its corresponding buffers to reduce the problem size. Then, we go into iterations of the alternating and interacting global optimization step and the partitioning step. The global optimization step places blocks based on simulated annealing using the B*-tree representation to minimize a given cost function. The partitioning step dissects the chip into two subregions, and the blocks are divided into two groups and are placed in respective subregions. The two steps repeat until each subregion contains at most a given number of blocks, defined by the ratio of the total block area to the chip area. At last, we refine the floorplan by perturbing blocks inside a subregion as well as in different subregions. Compared with the B*-tree based floorplanner alone, our method is more efficient and obtains significantly better results, with an average cost of only 51.8 % of that obtained by using the B*-tree alone, based on a set of real industrial flip-chip designs provided by leading companies

Deterministic analog circuit placement using hierarchically bounded enumeration and enhanced shape functions

Abstract — The analog placement algorithm Plantage, presented in this paper, generates placements for analog circuits with comprehensive placement constraints. Plantage is based on a hierarchically bounded enumeration of basic building blocks, using B*-trees. The practically relevant solution space is thereby enumerated quasi-complete. The sets of possible placements of the basic building blocks are represented and combined in a new efficient way, using enhanced shape functions. The result of Plantage is the Pareto front of placements with respect to different aspect ratios. The whole approach is deterministic, in contrast to existing analog placement algorithms. I

Routing congestion analysis and reduction in deep sub-micron VLSI design

Congestion is one of the main optimization objectives in global routing. However, the optimization performance is constrained because the cells are already fixed at this stage. Therefore, designer can save substantial time and resources by detecting and reducing congested regions during the planning stages. An efficient and yet accurate congestion estimation model is crucial to be included in the inner loop of floorplanning and placement design. In this dissertation, we mainly focus on routing congestion modeling and reduction during floorplanning and placement

Physical Planning and Uncore Power Management for Multi-Core Processors

For the microprocessor technology of today and the foreseeable future, multi-core is a key engine that drives performance growth under very tight power dissipation constraints. While previous research has been mostly focused on individual processor cores, there is a compelling need for studying how to efficiently manage shared resources among cores, including physical space, on-chip communication and on-chip storage. In managing physical space, floorplanning is the first and most critical step that largely affects communication efficiency and cost-effectiveness of chip designs. We consider floorplanning with regularity constraints that requires identical processing/memory cores to form an array. Such regularity can greatly facilitate design modularity and therefore shorten design turn-around time. Very little attention has been paid to automatic floorplanning considering regularity constraints because manual floorplanning has difficulty handling the complexity as chip core count increases. In this dissertation work, we investigate the regularity constraints in a simulated-annealing based floorplanner for multi/many core processor designs. A simple and effective technique is proposed to encode the regularity constraints in sequence-pair, which is a classic format of data representation in automatic floorplanning. To the best of our knowledge, this is the first work on regularity-constrained floorplanning in the context of multi/many core processor designs. On-chip communication and shared last level cache (LLC) play a role that is at least as equally important as processor cores in terms of chip performance and power. This dissertation research studies dynamic voltage and frequency scaling for on-chip network and LLC, which forms a single uncore domain of voltage and frequency. This is in contrast to most previous works where the network and LLC are partitioned and associated with processor cores based on physical proximity. The single shared domain can largely avoid the interfacing overhead across domain boundaries and is practical and very useful for industrial products. Our goal is to minimize uncore energy dissipation with little, e.g., 5% or less, performance degradation. The first part of this study is to identify a metric that can reflect the chip performance determined by uncore voltage/frequency. The second part is about how to monitor this metric with low overhead and high fidelity. The last part is the control policy that decides uncore voltage/frequency based on monitoring results. Our approach is validated through full system simulations on public architecture benchmarks

B*tree representation based thermal and variability aware floorplanning frame work

Master'sMASTER OF ENGINEERIN

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