FFTPL: An Analytic Placement Algorithm Using Fast Fourier Transform for Density Equalization

We propose a flat nonlinear placement algorithm FFTPL using fast Fourier transform for density equalization. The placement instance is modeled as an electrostatic system with the analogy of density cost to the potential energy. A well-defined Poisson's equation is proposed for gradient and cost computation. Our placer outperforms state-of-the-art placers with better solution quality and efficiency

Efficient quadratic placement for FPGAs.

Field Programmable Gate Arrays (FPGAs) are widely used in industry because they can implement any digital circuit on site simply by specifying programmable logic and their interconnections. However, this rapid prototyping advantage may be adversely affected because of the long compile time, which is dominated by placement and routing. This issue is of great importance, especially as the logic capacities of FPGAs continue to grow. This thesis focuses on the placement phase of FPGA Computer Aided Design (CAD) flow and presents a fast, high quality, wirelength-driven placement algorithm for FPGAs that is based on the quadratic placement approach. In this thesis, multiple iterations of equation solving process together with a linear wirelength reduction technique are introduced. The proposed algorithm efficiently handles the main problems with the quadratic placement algorithm and produces a fast and high quality placement. Experimental results, using twenty benchmark circuits, show that this algorithm can achieve comparable total wirelength and, on average, 5X faster run time when compared to an existing, state-of-the-art placement tool. This thesis also shows that the proposed algorithm delivers promising preliminary results in minimizing the critical path delay while maintaining high placement quality.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .X86. Source: Masters Abstracts International, Volume: 44-04, page: 1946. Thesis (M.A.Sc.)--University of Windsor (Canada), 2005

An integrated placement and routing approach

As the feature size continues scaling down, interconnects become the major contributor of signal delay. Since interconnects are mainly determined by placement and routing, these two stages play key roles to achieve high performance. Historically, they are divided into two separate stages to make the problem tractable. Therefore, the routing information is not available during the placement process. Net models such as HPWL, are employed to approximate the routing to simplify the placement problem. However, the good placement in terms of these objectives may not be routable at all in the routing stage because different objectives are optimized in placement and routing stages. This inconsistancy makes the results obtained by the two-step optimization method far from optimal;In order to achieve high-quality placement solution and ensure the following routing, we propose an integrated placement and routing approach. In this approach, we integrate placement and routing into the same framework so that the objective optimized in placement is the same as that in routing. Since both placement and routing are very hard problems (NP-hard), we need to have very efficient algorithms so that integrating them together will not lead to intractable complexity;In this dissertation, we first develop a highly efficient placer - FastPlace 3.0 for large-scale mixed-size placement problem. Then, an efficient and effective detailed placer - FastDP is proposed to improve global placement by moving standard cells in designs. For high-degree nets in designs, we propose a novel performance-driven topology design algorithm to generate good topologies to achieve very strict timing requirement. In the routing phase, we develop two global routers, FastRoute and FastRoute 2.0. Compared to traditional global routers, they can generate better solutions and are two orders of magnitude faster. Finally, based on these efficient and high-quality placement and routing algorithms, we propose a new flow which integrates placement and routing together closely. In this flow, global routing is extensively applied to obtain the interconnect information and direct the placement process. In this way, we can get very good placement solutions with guaranteed routability

MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning

Placement is an essential task in modern chip design, aiming at placing millions of circuit modules on a 2D chip canvas. Unlike the human-centric solution, which requires months of intense effort by hardware engineers to produce a layout to minimize delay and energy consumption, deep reinforcement learning has become an emerging autonomous tool. However, the learning-centric method is still in its early stage, impeded by a massive design space of size ten to the order of a few thousand. This work presents MaskPlace to automatically generate a valid chip layout design within a few hours, whose performance can be superior or comparable to recent advanced approaches. It has several appealing benefits that prior arts do not have. Firstly, MaskPlace recasts placement as a problem of learning pixel-level visual representation to comprehensively describe millions of modules on a chip, enabling placement in a high-resolution canvas and a large action space. It outperforms recent methods that represent a chip as a hypergraph. Secondly, it enables training the policy network by an intuitive reward function with dense reward, rather than a complicated reward function with sparse reward from previous methods. Thirdly, extensive experiments on many public benchmarks show that MaskPlace outperforms existing RL approaches in all key performance metrics, including wirelength, congestion, and density. For example, it achieves 60%-90% wirelength reduction and guarantees zero overlaps. We believe MaskPlace can improve AI-assisted chip layout design. The deliverables are released at https://laiyao1.github.io/maskplace

Analytical Solution of Poisson's Equation with Application to VLSI Global Placement

Poisson's equation has been used in VLSI global placement for describing the potential field caused by a given charge density distribution. Unlike previous global placement methods that solve Poisson's equation numerically, in this paper, we provide an analytical solution of the equation to calculate the potential energy of an electrostatic system. The analytical solution is derived based on the separation of variables method and an exact density function to model the block distribution in the placement region, which is an infinite series and converges absolutely. Using the analytical solution, we give a fast computation scheme of Poisson's equation and develop an effective and efficient global placement algorithm called Pplace. Experimental results show that our Pplace achieves smaller placement wirelength than ePlace and NTUplace3. With the pervasive applications of Poisson's equation in scientific fields, in particular, our effective, efficient, and robust computation scheme for its analytical solution can provide substantial impacts on these fields

Fast 3D Integrated Circuit Placement Methodology using Merging Technique

In the recent years the advancement in the field of microelectronics integrated circuit (IC) design technologies proved to be a boon for design and development of various advanced systems in-terms of its reduction in form factor, low power, high speed and with increased capacity to incorporate more designs. These systems provide phenomenal advantage for armoured fighting vehicle (AFV) design to develop miniaturised low power, high performance sub-systems. One such emerging high-end technology to be used to develop systems with high capabilities for AFVs is discussed in this paper. Three dimensional IC design is one of the emerging field used to develop high density heterogeneous systems in a reduced form factor. A novel grouping based partitioning and merge based placement (GPMP) methodology for 3D ICs to reduce through silicon vias (TSVs) count and placement time is proposed. Unlike state-of-the-art techniques, the proposed methodology does not suffer from initial overlap of cells during intra-layer placement which reduces the placement time. Connectivity based grouping and partitioning ensures less number of TSVs and merge based placement further reduces intra layer wire-length. The proposed GPMP methodology has been extensively against the IBMPLACE database and performance has been compared with the latest techniques resulting in 12 per cent improvement in wire-length, 13 per cent reduction in TSV and 1.1x improvement in placement time

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