Bus-driven floorplanning.

Law Hoi Ying.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 101-106).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- VLSI Design Cycle --- p.2Chapter 1.2 --- Physical Design Cycle --- p.6Chapter 1.3 --- Floorplanning --- p.10Chapter 1.3.1 --- Floorplanning Objectives --- p.11Chapter 1.3.2 --- Common Approaches --- p.12Chapter 1.3.3 --- Interconnect-Driven Floorplanning --- p.14Chapter 1.4 --- Motivations and Contributions --- p.15Chapter 1.5 --- Organization of the Thesis --- p.17Chapter 2 --- Literature Review on 2D Floorplan Representations --- p.18Chapter 2.1 --- Types of Floorplans --- p.18Chapter 2.2 --- Floorplan Representations --- p.20Chapter 2.2.1 --- Slicing Floorplan --- p.21Chapter 2.2.2 --- Non-slicing Floorplan --- p.22Chapter 2.2.3 --- Mosaic Floorplan --- p.30Chapter 2.3 --- Summary --- p.35Chapter 3 --- Literature Review on 3D Floorplan Representations --- p.37Chapter 3.1 --- Introduction --- p.37Chapter 3.2 --- Problem Formulation --- p.38Chapter 3.3 --- Previous Work --- p.38Chapter 3.4 --- Summary --- p.42Chapter 4 --- Literature Review on Bus-Driven Floorplanning --- p.44Chapter 4.1 --- Problem Formulation --- p.44Chapter 4.2 --- Previous Work --- p.45Chapter 4.2.1 --- Abutment Constraint --- p.45Chapter 4.2.2 --- Alignment Constraint --- p.49Chapter 4.2.3 --- Bus-Driven Floorplanning --- p.52Chapter 4.3 --- Summary --- p.53Chapter 5 --- Multi-Bend Bus-Driven Floorplanning --- p.55Chapter 5.1 --- Introduction --- p.55Chapter 5.2 --- Problem Formulation --- p.56Chapter 5.3 --- Methodology --- p.57Chapter 5.3.1 --- Shape Validation --- p.58Chapter 5.3.2 --- Bus Ordering --- p.65Chapter 5.3.3 --- Floorplan Realization --- p.72Chapter 5.3.4 --- Simulated Annealing --- p.73Chapter 5.3.5 --- Soft Block Adjustment --- p.75Chapter 5.4 --- Experimental Results --- p.75Chapter 5.5 --- Summary --- p.77Chapter 6 --- Bus-Driven Floorplanning for 3D Chips --- p.80Chapter 6.1 --- Introduction --- p.80Chapter 6.2 --- Problem Formulation --- p.81Chapter 6.3 --- The Representation --- p.82Chapter 6.3.1 --- Overview --- p.82Chapter 6.3.2 --- Review of TCG --- p.83Chapter 6.3.3 --- Layered Transitive Closure Graph (LTCG) --- p.84Chapter 6.3.4 --- Aligning Blocks --- p.85Chapter 6.3.5 --- Solution Perturbation --- p.87Chapter 6.4 --- Simulated Annealing --- p.92Chapter 6.5 --- Soft Block Adjustment --- p.92Chapter 6.6 --- Experimental Results --- p.93Chapter 6.7 --- Summary --- p.94Chapter 6.8 --- Acknowledgement --- p.95Chapter 7 --- Conclusion --- p.99Bibliography --- p.10

Efficient approaches in interconnect-driven floorplanning.

Lai Tsz Wai.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 123-129).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- VLSI Design Cycle --- p.2Chapter 1.2 --- Physical Design Cycle --- p.4Chapter 1.3 --- Floorplanning --- p.7Chapter 1.3.1 --- Types of Floorplan and Floorplan Representations --- p.11Chapter 1.3.2 --- Interconnect-driven Floorplanning --- p.13Chapter 1.4 --- Motivations and Contributions --- p.17Chapter 1.5 --- Organization of this Thesis --- p.18Chapter 2 --- Literature Review on Floorplan Representation --- p.20Chapter 2.1 --- Slicing Floorplan Representation --- p.20Chapter 2.1.1 --- Normalized Polish Expression --- p.20Chapter 2.2 --- Non-slicing Floorplan Representations --- p.21Chapter 2.2.1 --- Sequence Pair (SP) --- p.21Chapter 2.2.2 --- Bounded-sliceline Grid (BSG) --- p.23Chapter 2.2.3 --- O-tree --- p.25Chapter 2.2.4 --- B*-tree --- p.26Chapter 2.3 --- Mosaic Floorplan Representations --- p.28Chapter 2.3.1 --- Corner Block List (CBL) --- p.28Chapter 2.3.2 --- Twin Binary Trees (TBT) --- p.31Chapter 2.3.3 --- Twin Binary Sequences (TBS) --- p.32Chapter 2.4 --- Summary --- p.34Chapter 3 --- Literature Review on Interconnect Optimization in Floorplan- ning --- p.37Chapter 3.1 --- Wirelength Estimation --- p.37Chapter 3.2 --- Congestion Optimization --- p.38Chapter 3.2.1 --- Integrated Floorplanning and Interconnect Planning --- p.41Chapter 3.2.2 --- Multi-layer Global Wiring Planning (GWP) --- p.43Chapter 3.2.3 --- Estimating Routing Congestion using Probabilistic Anal- ysis --- p.44Chapter 3.2.4 --- Congestion Minimization During Placement --- p.46Chapter 3.2.5 --- Modelling and Minimization of Routing Congestion --- p.48Chapter 3.3 --- Buffer Planning --- p.49Chapter 3.3.1 --- Buffer Clustering with Feasible Region --- p.51Chapter 3.3.2 --- Routability-driven Repeater Clustering Algorithm with Iterative Deletion --- p.55Chapter 3.3.3 --- Planning Buffer Locations by Network Flow --- p.58Chapter 3.3.4 --- Buffer Planning using Integer Multicommodity Flow --- p.60Chapter 3.3.5 --- Buffer Planning Problem using Tile Graph --- p.60Chapter 3.3.6 --- Probabilistic Analysis for Buffer Block Planning --- p.62Chapter 3.3.7 --- Fast Buffer Planning and Congestion Optimization --- p.63Chapter 3.4 --- Summary --- p.66Chapter 4 --- Congestion Evaluation: Wire Density Model --- p.68Chapter 4.1 --- Introduction --- p.68Chapter 4.2 --- Overview of Our Floorplanner --- p.70Chapter 4.3 --- Wire Density Model --- p.71Chapter 4.3.1 --- Computation of Ni --- p.72Chapter 4.3.2 --- Computation of Pi --- p.74Chapter 4.3.3 --- Usage of Mirror TBT --- p.76Chapter 4.4 --- Implementation --- p.76Chapter 4.4.1 --- Efficient Calculation of Ni --- p.76Chapter 4.4.2 --- Solving the LCA Problem Efficiently --- p.81Chapter 4.4.3 --- Cost Function --- p.81Chapter 4.4.4 --- Complexity --- p.81Chapter 4.5 --- Experimental Results --- p.82Chapter 4.6 --- Conclusion --- p.83Chapter 5 --- Buffer Planning: Simple Buffer Planning Method --- p.85Chapter 5.1 --- Introduction --- p.85Chapter 5.2 --- Variable Interval Buffer Insertion Constraint --- p.87Chapter 5.3 --- Overview of Our Floorplanner --- p.88Chapter 5.4 --- Buffer Planning --- p.89Chapter 5.4.1 --- Feasible Grids --- p.89Chapter 5.4.2 --- Table Look-up Approach --- p.89Chapter 5.5 --- Implementation --- p.91Chapter 5.5.1 --- Building the Look-up Tables --- p.91Chapter 5.5.2 --- An Example of Look-up Table Construction --- p.94Chapter 5.5.3 --- A Faster Approach for Building the Look-up Tables --- p.101Chapter 5.5.4 --- An Example of the Faster Look-up Table Construction --- p.105Chapter 5.5.5 --- I/O Pin Locations --- p.106Chapter 5.5.6 --- Cost Function --- p.110Chapter 5.5.7 --- Complexity --- p.111Chapter 5.6 --- Experimental Results --- p.112Chapter 5.6.1 --- Selected Value for A --- p.112Chapter 5.6.2 --- Performance of Our Floorplanner --- p.113Chapter 5.7 --- Conclusion --- p.116Chapter 6 --- Conclusion --- p.118Chapter A --- An Efficient Algorithm for the Least Common Ancestor Prob- lem --- p.120Bibliography --- p.12

A framework for fine-grain synthesis optimization of operational amplifiers

This thesis presents a cell-level framework for Operational Amplifiers Synthesis (OASYN) coupling both circuit design and layout. For circuit design, the tool applies a corner-driven optimization, accounting for on-chip performance variations. By exploring the process, voltage, and temperature variations space, the tool extracts design worst case solution. The tool undergoes sensitivity analysis along with Pareto-optimality to achieve required specifications. For layout phase, OASYN generates a DRC proved automated layout based on a sized circuit-level description. Morata et al. (1996) introduced an elegant representation of block placement called sequence pair for general floorplans (SP). Like TCG and BSG, but unlike O-tree, B*tree, and CBL, SP is P-admissible. Unlike SP, TCG supports incremental update during operation and keeps the information of the boundary modules as well as their relative positions in the representation. Block placement algorithms that are based on SP use heuristic optimization algorithms, e.g., simulated annealing where generation of large number of sequence pairs are required. Therefore a fast algorithm is needed to generate sequence pairs after each solution perturbation. The thesis presents a new simple and efficient O(n) runtime algorithm for fast realization of incremental update for cost evaluation. The algorithm integrates sequence pair and transitive closure graph advantages into TCG-S* a superior topology update scheme which facilitates the search for optimum desired floorplan. Experiments show that TCG-S* is better than existing works in terms of area utilization and convergence speed. Routing-aware placement is implemented in OASYN, handling symmetry constraints, e.g., interdigitization, common centroid, along with congestion elimination and the enhancement of placement routability

Fixed-outline bus-driven floorplanning.

Jiang, Yan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 87-92).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Physical Design --- p.2Chapter 1.2 --- Floorplanning --- p.6Chapter 1.2.1 --- Floorplanning Objectives --- p.7Chapter 1.2.2 --- Common Approaches --- p.8Chapter 1.3 --- Motivations and Contributions --- p.14Chapter 1.4 --- Organization of the Thesis --- p.15Chapter 2 --- Literature Review on BDF --- p.17Chapter 2.1 --- Zero-Bend BDF --- p.17Chapter 2.1.1 --- BDF Using the Sequence-Pair Representation --- p.17Chapter 2.1.2 --- Using B*-Tree and Fast SA --- p.20Chapter 2.2 --- Two-Bend BDF --- p.22Chapter 2.3 --- TCG-Based Multi-Bend BDF --- p.25Chapter 2.3.1 --- Placement Constraints for Bus --- p.26Chapter 2.3.2 --- Bus Ordering --- p.28Chapter 2.4 --- Bus-Pin-Aware BDF --- p.30Chapter 2.5 --- Summary --- p.33Chapter 3 --- Fixed-Outline BDF --- p.35Chapter 3.1 --- Introduction --- p.35Chapter 3.2 --- Problem Formulation --- p.36Chapter 3.3 --- The Overview of Our Approach --- p.36Chapter 3.4 --- Partitioning --- p.37Chapter 3.4.1. --- The Overview of Partitioning --- p.38Chapter 3.4.2 --- Building a Hypergraph G --- p.39Chapter 3.5 --- Floorplaiining with Bus Routing --- p.43Chapter 3.5.1 --- Find Bus Routes --- p.43Chapter 3.5.2 --- Realization of Bus Routes --- p.48Chapter 3.5.3 --- Details of the Annealing Process --- p.50Chapter 3.6 --- Handle Fixed-Outline Constraints --- p.52Chapter 3.7 --- Bus Layout --- p.52Chapter 3.8 --- Experimental Results --- p.56Chapter 3.9 --- Summary --- p.61Chapter 4 --- Fixed-Outline BDF with L-shape bus --- p.63Chapter 4.1 --- Introduction --- p.63Chapter 4.2 --- Problem Formulation --- p.64Chapter 4.3 --- Our Approach --- p.65Chapter 4.3.1 --- Bus Routability Checking --- p.67Chapter 4.3.2 --- Details of the Annealing Process --- p.79Chapter 4.4 --- Experimental Results --- p.79Chapter 4.5 --- Summary --- p.82Chapter 5 --- Conclusion --- p.85Bibliography --- p.9

Thermal aware design techniques for multiprocessor architectures in three dimensions

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 28-11-2013Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

Layer assignment and routing optimization for advanced technologies

As VLSI technology scales to deep sub-micron and beyond, it becomes increasingly challenging to achieve timing closure for VLSI design. Since a complete design flow consists of several phases, such as logic synthesis, placement, and routing, interconnect synthesis plays an important role which includes buffer insertion/sizing and timing-driven routing. Although progress has been achieved by many advanced routing techniques, the following aspects can be exploited sufficiently for further improvement: (1) incremental layer assignment for timing optimization; (2) signal routing with the requirement of regularity; (3) power-efficient optical-electrical interconnect paradigm. Thus, to perform the layer assignment and routing optimization for advanced technologies, an automated routing engine in a global view is essential to benefit the interconnect design while satisfying specific requirements. This dissertation proposes a set of algorithms and methodology on layer assignment and routing optimization for advanced technologies. The research includes two timing-driven incremental layer assignment approaches, synergistic topology generation and routing synthesis for signal groups, and optical-electrical routing design for power efficiency. For incremental layer assignment, most of the conventional approaches target via minimization but neglect the timing issues. Meanwhile, via delays are ignored but should be considered in emerging technology nodes. Then two timing-driven incremental layer assignment frameworks are proposed, where all the nets are solved simultaneously with the integration of via delays: (1) optimization of the total sum of net delays and reduction of slew violations; (2) minimization of critical path timing in selected nets. For on-chip signal routing, the bundled bits in one group may have different pin locations, but they have to be routed in a regular manner by sharing common topologies. Very few previous works target inter-bit regularity via multi-layer topology selection. Furthermore, the routability and wire-length of the signal bits should also be optimized. Then an advanced synergistic routing engine is promoted, which is able to not only control routability and wire-length but also guide each bit routing intelligently for design regularity. For optical-electrical co-design routing, optical interconnect shows its advantage due to the dominance of bandwidth-distance-power properties. The previous works lack a detailed exploration of optical-electrical co-design for on-chip interconnects. During the transmission, signal quality can be affected by various loss sources and Electrical to Optical (EO)/Optical to Electrical (OE) conversion overheads should also be considered. Then a power-efficient routing flow for on-chip signals is presented, where optical connections can collaborate with electrical wires seamlessly. The effectiveness of proposed algorithms and techniques is demonstrated in this dissertation. These approaches are able to achieve the improvements regarding specific metrics and eventually benefit the routing flow.Electrical and Computer Engineerin

Simulated Annealing

The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine

Timing-Driven Macro Placement

Placement is an important step in the process of finding physical layouts for electronic computer chips. The basic task during placement is to arrange the building blocks of the chip, the circuits, disjointly within a given chip area. Furthermore, such positions should result in short circuit interconnections which can be routed easily and which ensure all signals arrive in time. This dissertation mostly focuses on macros, the largest circuits on a chip. In order to optimize timing characteristics during macro placement, we propose a new optimistic timing model based on geometric distance constraints. This model can be computed and evaluated efficiently in order to predict timing traits accurately in practice. Packing rectangles disjointly remains strongly NP-hard under slack maximization in our timing model. Despite of this we develop an exact, linear time algorithm for special cases. The proposed timing model is incorporated into BonnMacro, the macro placement component of the BonnTools physical design optimization suite developed at the Research Institute for Discrete Mathematics. Using efficient formulations as mixed-integer programs we can legalize macros locally while optimizing timing. This results in the first timing-aware macro placement tool. In addition, we provide multiple enhancements for the partitioning-based standard circuit placement algorithm BonnPlace. We find a model of partitioning as minimum-cost flow problem that is provably as small as possible using which we can avoid running time intensive instances. Moreover we propose the new global placement flow Self-Stabilizing BonnPlace. This approach combines BonnPlace with a force-directed placement framework. It provides the flexibility to optimize the two involved objectives, routability and timing, directly during placement. The performance of our placement tools is confirmed on a large variety of academic benchmarks as well as real-world designs provided by our industrial partner IBM. We reduce running time of partitioning significantly and demonstrate that Self-Stabilizing BonnPlace finds easily routable placements for challenging designs – even when simultaneously optimizing timing objectives. BonnMacro and Self-Stabilizing BonnPlace can be combined to the first timing-driven mixed-size placement flow. This combination often finds placements with competitive timing traits and even outperforms solutions that have been determined manually by experienced designers

Techniques de routage pseudo-aléatoire pour une application micro-électronique

Résumé La problématique de routage est très actuelle. On en trouve des applications dans les GPS, les prévisions de trafic routier, mais aussi pour le prototypage sur FPGA, la fabrication de puces électroniques ou le trafic TCP/IP sur Internet. On trouve des publications sur le sujet depuis plusieurs dizaines d'années, mais on observe actuellement une recrudescence confirmant l'actualité, l'importance et la complexité de ce problème. Cette thèse concerne le routage et ses ressources pour une application dans un nouveau type de système micro-électronique, nommé le WaferBoardTM . Son noyau consiste en un circuit électronique intégré à l'échelle d'une tranche de silicium (wafer). Peu d'applications commerciales de la micro-électronique ont exploité ce niveau d'intégration. Ce système de prototypage rapide vise à réduire d'un ou deux ordres de grandeur le temps de développement de systèmes électroniques. Il nécessite un ensemble d'outils logiciel de support, dont un outil de routage très rapide, capable de produire des solutions valables en des temps de l'ordre de la minute, et de certaines fonctionnalités spécifiques, l'équilibrage de délai ou le reroutage à la volée, au sein d'une netlist déjà routée. La problématique de routage pour cette application peut être imagée comme suit. Étant donné un réseau routier régulier (les routes d’Amériques du Nord en version cartésienne par exemple) et 100,000 voitures au départ lundi à 8h a.m. dans tout le pays avec des sources et destinations très variées; calculer les chemins pour toutes les voitures de telle sorte qu'aucune ne prenne la même route dans la journée. Il est 7h59 a.m, vous avez 1 minute, et des ponts sont inaccessibles pour travaux, en voici la liste. Cet exemple simpliste donne une idée des ordres de grandeurs de la problématique de routage que l'on cherche à résoudre pour cette application. Un algorithme de routage prend en paramètres deux structures de données : un graphe (ou réseau d'interconnexions) constitué de n\oe{}uds (sommets) et d'arcsUn arc relie deux sommets du graphe, et une netlistDans ce contexte, un netlist réfère à une liste d'interconnexions entre composants, liste de n\oe{}uds électriques dont les points de départ et d'arrivée sont positionnés géographiquement. Ainsi, au lieu de voitures, il s'agit de router des signaux électriques dont les points de départ et d'arrivée sont dictés par la position des broches des composants placés sur le système de prototypage. Un réseau régulier maillé mufti-dimensionnel (plus généralement appelé « réseau d'interconnexions ») sert de réseau routier dont certaines routes sont défectueuses, des ponts inaccessibles. En effet, le réseau d'interconnexions est un circuit électronique intégré à l'échelle d'une tranche de silicium complète, ce qui implique la présence de défectuosités au sein de chaque circuit fabriqué. Contrairement aux circuits électroniques classiques, où chacun est testé et les défectueux écartés, une intégration à l'échelle de la tranche demande de fortes redondances au sein du circuit pour minimiser le taux de rejets. Pour l'application du WaferBoard, un certain nombre d'éléments du réseau d'interconnexions seront fort probablement défectueux sur chaque circuit produit; l'algorithme de routage se doit de prendre en compte ces éléments très particuliers. Cette contrainte ne se retrouve pas dans les applications plus classiques des routeurs que l'on retrouve dans les PCB, circuits FPGA ou circuits VLSI. D'autres contraintes s'appliquent à ce projet particulier : la latence induite par la technologie est environ un ordre de grandeur plus importante que celle dans les circuits sur PCB, ce qui impose un routage orienté vers sa réduction.----------Abstract The routing problem is very actual. Applications are found in GPS, road traffic forecast, but also for prototyping on FPGA, or TCP/IP traffic on the Internet. Publications on the subject have existed for several decades, but new publications keep appearing, confirming the importance and complexity of the problem. This thesis deals with routing and the resources it requires for a new category of micro-electronic applications, called the WaferBoard. It is an electronic circuit integrated at the wafer scale. Few commercial applications of micro-electronics have exploited this level of integration. This rapid prototyping system aims at reducing by one or two orders of magnitude the development time of digital circuits. It requires a very fast routing tool, capable of producing viable solutions in a few minutes, with dedicated functionality such as balancing delays and rerouting on the fly parts of a netlist. The routing problem for this application can be pictured as follows. Given a regular road network of the size of north america, if 100.000 cars were to start Monday 8 a.m. across the continent with a wide variety of sources and destinations; the challenge is to compute paths for all cars so none of them take the same route that day. It is 7:59 am, you have 1 minute, and some bridges are under road work: here is the list. This simplistic example gives an idea of the orders of magnitude of the problem that need to be solved for this application. A routing algorithm takes as input: a graph (or interconnection network) made of nodes and edges, and a netlst, a list of electrical nodes with starting and ending points physically placed. Therefore, instead of cars, the problem consists of routing electrical signals with points of departure and arrival dictated by the pin position of components placed on the prototyping system. A regular, multi-dimensional mesh (also called "interconnection network") serves as a road network, which contains defective roads and inaccessible bridges. Indeed, the interconnection network is an electronic circuit integrated across a full wafer, implying the presence of defects within each manufactured circuit. Unlike conventional electronic circuits, where each is tested and defective ones are set apart, wafer scale integrated applications require lots of redundancy in the circuit to minimize the rejection rate. In the WaferBoard, a number of elements of the interconnection network will be defective in each circuit; the routing algorithm must take into account these very specific elements. This constraint is not found in the classic applications of routers found in PCB, FPGA or VLSI circuits. Other restrictions apply to this particular project: the latency induced by the technology is about one order of magnitude greater than that in the circuits of PCBs, which requires a routing oriented towards computation time reduction. This constraint partly explains the network architecture used. Within the WaferIC, the shortest distance is not necessarily the one that offers the smallest latency. This property of the network complexifies the routing problem. Balancing delays within a group of arbitrary size nets is a necessary feature of the routing algorithm, and the difficulty is amplified by the computation time limit. Indeed, the interest of the application is to reduce the time for a user to test a circuit: the time of setup is extremely short, and estimated at a few minutes only