Nanometer VLSI placement and optimization for multi-objective design closure

In a VLSI physical synthesis flow, placement directly defines the interconnection, which affects many other design objectives, such as timing, power consumption, congestion, and thermal issues. With the scaling of technology, the relative interconnect delay increases dramatically. As a result, placement has become a bottleneck in deep sub-micron physical synthesis. In this dissertation, I propose several optimization algorithms from global placement, placement migration, timing driven placements, to incremental power optimizations for multi-objective VLSI design closure. The first work is DPlace, a new global placement algorithm that scales well to the modern large-scale circuit placement problems. DPlace simulates the natural diffusion process to spread cells smoothly over the placement region, and uses both analytical and discrete techniques to improve the wire length. However, global placement is never sufficient for multi-objective design closure, a variety of design objectives have to be improved incrementally, such as timing, routing congestion, signal integrity, and heat distribution. Placement migration is a critical step to address the cell overlaps appearing during incremental optimizations. To achieve high placement stability, I propose a computational geometry based placement migration flow to cope with placement changes, and a new stability metric to measure the “similarity” between two placements accurately. Our placement migration algorithm has clear advantage over conventional legalization algorithms such that the neighborhood characteristics of the original placement are preserved. For timing closure in high performance designs, I present a linear programming based incremental timing driven placement to improve the timing on critical paths directly. I further present an efficient timing driven placement algorithm (Pyramids). Two formulations of Pyramids are proposed, which are suitable for different optimization stages in a physical synthesis flow. Both approaches find the optimal location for timing of a cell in constant time, through computational geometry based approaches. For fast convergence of design closure, placement should be integrated with other optimization techniques. I propose to combine placement, gate sizing and Vt swapping techniques to reduce the total power consumption, especially the leakage power, which is becoming increasingly critical for nanometer VLSI design closure.Electrical and Computer Engineerin

Custom Cell Placement Automation for Asynchronous VLSI

Asynchronous Very-Large-Scale-Integration (VLSI) integrated circuits have demonstrated many advantages over their synchronous counterparts, including low power consumption, elastic pipelining, robustness against manufacturing and temperature variations, etc. However, the lack of dedicated electronic design automation (EDA) tools, especially physical layout automation tools, largely limits the adoption of asynchronous circuits. Existing commercial placement tools are optimized for synchronous circuits, and require a standard cell library provided by semiconductor foundries to complete the physical design. The physical layouts of cells in this library have the same height to simplify the placement problem and the power distribution network. Although the standard cell methodology also works for asynchronous designs, the performance is inferior compared with counterparts designed using the full-custom design methodology. To tackle this challenge, we propose a gridded cell layout methodology for asynchronous circuits, in which the cell height and cell width can be any integer multiple of two grid values. The gridded cell approach combines the shape regularity of standard cells with the size flexibility of full-custom layouts. Therefore, this approach can achieve a better space utilization ratio and lower wire length for asynchronous designs. Experiments have shown that the gridded cell placement approach reduces area without impacting the routability. We have also used this placer to tape out a chip in a 65nm process technology, demonstrating that our placer generates design-rule clean results

Flow-based Partitioning and Fast Global Placement in Chip Design

VLSI placement is one of the major steps in the chip design process and an interesting subject of research in industry and academia. Recent chips consist of several millions of circuits connected by millions of nets. The classical placement objective of finding positions for circuits and minimizing netlength among them is an ongoing issue in optimization of chip performance. The increasing instance sizes, the tightness of timing and routability constraints impose a real challenge to the design flows and the designers, which often cannot be addressed properly without considering them explicitly within the placement. Many of the complex design methodologies follow an iterative approach, using placement several times in this process. Thus, placement runtime has a severe impact on the turnaround time in chip development. The major contributios of this thesis deal with the global placement, a common relaxation of the placement problem, which computes rough positions of the circuits minimizing the total length of wires to interconnect the. Based on the idea of subsequent quadratic netlength minimization and partitioning, as in BonnPlace [BrennerStruzynaVygen:2008], we present several new algorithms, generalized data structures and a completely new implementation of this top-down placement scheme. We introduce and formalize the concept of movebounds which are position constraints on subsets of cells. Movebounds, which can be regarded as mandatory or soft constraints, provide a mechanism to explicitly incorporate movement constraints to the placement which result from issues of timing, power and routability. With inclusive movebounds, such restrictions can be assigned to groups of circuits without any influence to other placeable objects. The other constraints, namely the exclusive movebounds, are of particular interest for semi-hierarchical approaches, as they can be used to obtain a flat view of the design and prevent cells from being placed into hierarchy units. Both provide a toolbox to the designer and allow the control of particular circuit sets without netlist manipulations. We also present a top-down partitioning scheme and extend the legalization algorithm of [BrennerVygen:2004] to be able to deal with millions of cells and dozens of movebounds efficiently. The presented algorithm can handle different types of overlapping movebounds, even in legalization, and produces significantly better results than a modern industrial tool. We present a novel partitioning algorithm for global placement. Unlike previous iterative and recursive approaches, the new method provides a global view of the problem using a novel MinCostFlow model with extremely fast and highly parallelizable local realization steps. The new flow-based partitioning can address density targets much more accurately and lowers the risk of density violations. The presented MinCostFlow model does not depend on the number of cells, making it highly interesting for large and huge designs. Moreover, the embedded flow structure responds to the chip's floorplan much better than the classical global partitioning approach. Another significant advantage of this algorithm is the fact that it can be applied to any initial placement and guarantees a feasible (fractional) solution (if one exists), improving the tool's reliability, even with movebounds and starting from placements with significant density violations. Using this method we can extend the congestion-driven placement to a combined movement, density adjustment, and cell size inflation approach. This method is able to handle movebounds and guarantees to resolve density overloads properly. Flow-based partitioning creates the opportunity of applying local, density unaware, optimization steps within global placement and allows it to break the strict recursive structure of levels and save runtime. The extended flexibility and runtime improvement are not the only advantages. The proposed flow realization, which is a combination of local quadratic programs and local partitioning, does not only yield a runtime improvement, but also seems to merge connectivity information to partitioning in a much better way than the old recursive partitioning approach. The new flow-based partitioning helps to significantly improve the results of our placement also in terms of netlength. We provide fast data structures for hierarchically clustered netlists and extend the net models Clique and Star to be applied within the clustered netlists efficiently. We show how shared-memory parallelization can be used for speeding up various routines in placement, without the loss of repeatability. In addition, we commit ourselves to the clustering problem, finding circuit groups which should be placed in the vicinity of each other. In order to provide global information for a fast bottom-up clustering, we propose to incorporate connectivity information using random walks. To this end, we show how the hitting times can be efficiently retrieved from large netlist hypergraphs. Due to the proposed model, parallel computation on sparse, shared-memory matrices can be used for computing hitting times to several targets simultaneously. Combined with a bottom-up clustering, even our preliminary approach significantly outperforms the popular BestChoice} algorithm [Nam et al. 2005]. We conclude this thesis by providing several experimental results on a large testbed of real-world chips and benchmarks demonstrating the performance of our tool. Without movebounds, our tool performs as good as a state-of-the-art force directed placer, but is more than 5x faster. We achieve the same speedup over the old BonnPlace, but produce significantly better results, on average more than 8%. With movebounds, our placements are more than 30% shorter compairing to the force-directed placer and our tool is 9x-20x faster. Our tool also produces the best results on the latest ISPD 2006 placement benchmarks

Placement for fast and reliable through-silicon-via (TSV) based 3D-IC layouts

The objective of this research is to explore the feasibility of addressing the major performance and reliability problems or issues, such as wirelength, stress-induced carrier mobility variation, temperature, and quality trade-offs, found in three-dimensional integrated circuits (3D ICs) that use through-silicon vias (TSVs) at placement stage. Four main works that support this goal are included. In the first work, wirelength of TSV-based 3D ICs is the main focus. In the second work, stress-induced carrier mobility variation in TSV-based 3D ICs is examined. In the third work, temperature inside TSV-based 3D ICs is investigated. In the final work, the quality trade-offs of TSV-based 3D-IC designs are explored. In the first work, a force-directed, 3D, and gate-level placement algorithm that efficiently handles TSVs is developed. The experiments based on synthesized benchmarks indicate that the developed algorithm helps generate GDSII layouts of 3D-IC designs that are optimized in terms of wirelength. In addition, the impact of TSVs on other physical aspects of 3D-IC designs is also studied by analyzing the GDSII layouts. In the second work, the model for carrier mobility variation caused by TSV and STI stresses is developed as well as the timing analysis flow considering the stresses. The impact of TSV and STI stresses on carrier mobility variation and performance of 3D ICs is studied. Furthermore, a TSV-stress-driven, force-directed, and 3D placement algorithm is developed. It exploits carrier mobility variation, caused by stress around TSVs after fabrication, to improve the timing and area objectives during placement. In addition, the impact of keep-out zone (KOZ) around TSVs on stress, carrier mobility variation, area, wirelength, and performance of 3D ICs is studied. In the third work, two temperature-aware global placement algorithms are developed. They exploit die-to-die thermal coupling in 3D ICs to improve temperature during placement. In addition, a framework used to evaluate the results from temperature-aware global placements is developed. The main component of the framework is a GDSII-level thermal analysis that considers all structures inside a TSV-based 3D IC while computing temperature. The developed placers are compared with several state-of-the-art placers published in recent literature. The experimental results indicate that the developed algorithms help improve the temperature of 3D ICs effectively. In the final work, three block-level design styles for TSV-based die-to-wafer bonded 3D ICs are discussed. Several 3D-IC layouts in the three styles are manually designed. The main difference among these layouts is the position of TSVs. Finally, the area, wirelength, timing, power, temperature, and mechanical stress of all layouts are compared to explore the trade-offs of layout quality.PhDCommittee Chair: Lim, Sung Kyu; Committee Member: Bakir, Muhannad; Committee Member: Kim, Hyesoon; Committee Member: Mukhopadhyay, Saibal; Committee Member: Swaminathan, Madhava

The IPS fidelity scale as a guideline to implement Supported Employment

info:eu-repo/semantics/publishe

Modern FPGA placement techniques with hardware acceleration

In deep sub-micron technology nodes, Application-Specific Integrated Circuits (ASICs) are becoming expensive to design and manufacture. For this reason, Field Programmable Gate Arrays (FPGAs), which are general purpose and flexible programmable hardware, are gaining more design wins in low volume and fast evolving applications. Modern FPGAs are becoming popular in high performance data analytics, search engines, autonomous cars, communication and networking applications. FPGAs are also accompanied with a complete Computer-Aided Design (CAD) toolchain, that is used to optimally map and fit the design applications or workloads onto the underlying target FPGA device. These design applications mapped onto the FPGA demand high maximum achievable clock frequency (Fmax) and low power consumption while maintaining a low compilation time, which is a major hindrance in widespread adoption of FPGAs. The focus of this Ph.D. dissertation is the placement problem for FPGAs, which takes a major portion of the FPGA CAD tool runtime. A new algorithm for spreading cells during FPGA global placement is proposed, which achieves better wirelength and routing congestion and takes less runtime than the algorithm used in the state-of-the-art academic FPGA placer. We also propose FPGA acceleration of various subsystems of an analytic global placement algorithm, including wirelength gradient computation and spreading, which achieves significant speedup over the multi-threaded CPU version. A new detailed placement algorithm is proposed, which offers better tradeoff between quality and runtime compared to existing methods. This algorithm is also accelerated on a GPU and an FPGA, achieving significant speedup over multi-threaded CPU implementation. Another detailed placement algorithm is also proposed which physically re-aligns timing critical paths and improves Fmax with minimal runtime overhead. Both of these algorithms for detailed placement have shown good results on industrial benchmarks and have been integrated into an industrial FPGA CAD tool flowElectrical and Computer Engineerin