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Im Vergleich zum digitalen Layoutentwurf weist der analoge Layoutentwurf einen wesentlich geringeren Automatisierungsgrad auf. Dies gilt insbesondere für den Layoutentwurf von Hochfrequenzschaltungen, wo Einflüsse der lokalen Layoutumgebung besonders zu berücksichtigen sind. Bei dieser sog. Kontextabhängigkeit geraten sowohl Optimierungsalgorithmen als auch herkömmliche Generatoransätze schnell an Grenzen. In dieser Arbeit wird eine funktionale Erweiterung des bekannten Generatorprinzips eingesetzt, die es erlaubt, Informationen aus der Layoutumgebung der Instanz in die Layoutgenerierung einzubeziehen. Mit dieser sog. kontextbasierten PCell gelingt die Automatisierung konkreter, bisher nur manuell lösbarer Probleme des Layoutentwurfs von Hochfrequenzschaltungen. Die Arbeit zeigt das Potential kontextbasierter PCells für die weitere Steigerung des Automatisierungsgrades im analogen Layoutentwurf.
Analog integrated circuit sizing still relies heavily on human expert knowledge as previous automation approaches have not found wide-spread acceptance in industry. One strand, the optimization-based automation, is often discarded due to inflated constraining setups, infeasible results or excessive run times. To address these deficits, this work proposes a alternative optimization flow featuring a designer’s intuition for feasible design spaces through integration of expert knowledge based on the gm/ID-method. Moreover, the extensive run times of simulation-based optimization flows are overcome by incorporating computationally efficient machine learning methods. Neural network surrogate models predicting eleven performance parameters increase the evaluation speed by 3 400× on average compared to a simulator. Additionally, they enable the use of optimization algorithms dependent on automatic differentiation, that would otherwise be unavailable in this field. First, an up to 4× more efficient way for sampling training data based on the aforementioned space is detailed. After presenting the architecture and training effort regarding the surrogate models, they are employed as part of the objective function for sizing three operational amplifiers with three different optimization algorithms. Additionally, the benefits of using the gm/ID-method become evident when considering technology migration, as previously found solutions may be reused for other technologies.
In diesem Artikel wird ein neu entwickeltes Werkzeug zur Dimensionierung von Bonddrähten im ASIC-Entwurf vorgestellt. Die Berücksichtigung aller Einflussfaktoren erlaubt eine gegenüber Handrechnungen optimierte Auslegung der Bondanordnung. Dies ermöglicht zum einen die Absicherung gegen Degradationseffekte bis hin zum Durchbrennen und garantiert so die Zuverlässigkeit über die gesamte Lebensdauer. Zum anderen wird eine aus Zuverlässigkeitserwägungen resultierende Überdimensionierung vermieden.
Das Werkzeug erlaubt die Kalkulation aller für die Auslegung von Bonddrähten relevanten Parameter. Je nach Kontext der Aufgabenstellung lassen sich die Stromtragfähigkeit für Dauerstrom oder Pulsstrombelastung, kritische Temperaturen oder die maximale Bonddrahtlänge als Ausgabegrößen berechnen. Durch diese Flexibilität und die benutzerfreundliche Integration in eine industrielle Entwicklungsumgebung ist der „Bond-Rechner“ im gesamten Entwurfsverlauf einsetzbar und leistet wertvolle Hilfestellung von ersten Abschätzungen in frühen Entwurfsphasen bis hin zur abschließenden Verifikation.
There is still a great reliance on human expert knowledge during the analog integrated circuit sizing design phase due to its complexity and scale, with the result that there is a very low level of automation associated with it. Current research shows that reinforcement learning is a promising approach for addressing this issue. Similarly, it has been shown that the convergence of conventional optimization approaches can be improved by transforming the design space from the geometrical domain into the electrical domain. Here, this design space transformation is employed as an alternative action space for deep reinforcement learning agents. The presented approach is based entirely on reinforcement learning, whereby agents are trained in the craft of analog circuit sizing without explicit expert guidance. After training and evaluating agents on circuits of varying complexity, their behavior when confronted with a different technology, is examined, showing the applicability, feasibility as well as transferability of this approach.
In practice, the use of layout PCells for analog IC design has not advanced beyond primitive devices and simple modules. This paper introduces a Constraint-Administered PCell-Applying Blocklevel Layout Engine (CAPABLE) which permits PCells to access their context, thus enabling a true "bottom-up" development of complex parameterized modules. These modules are integrated into the design flow with design constraints and applied by an execution cockpit via an automatically built layout script. The practical purpose of CAPABLE is to easily generate full-custom block layouts for given schematic circuits. Perspectively, our results inspire a whole new conception of PCells that can not only act (on demand), but also react (to environmental changes) and interact (with each other).
Eine neue Methode zur Berechnung von Temperaturen in Bonddrähten umgeben von einem endlichen Mold wird vorgestellt. Sie ist schneller als die übliche Finite Elemente-Methode (FEM), während sie vergleichbare Resultate produziert. Für manche Parameter funktioniert unsere Methode, während die FEM-Methode versagt. Der Algorithmus ist im sogenannten Bondrechner implementiert, der eine leicht zu benutzende Oberfläche für Designer von mikroelektronischen Systemen bereitstellt. Seine Anwendung hat das Potential, die Zuverlässigkeit von Bonddrähten zu verbessern. Ein nichtidealer Parameter für den Wärmetransfer vom Bonddraht zum Mold-Package wurde ebenfalls berücksichtigt. Dieser Parameter ändert sich wahrscheinlich unter Alterseinflüssen und ist daher sehr wichtig für Zuverlässigkeits-Schätzungen. In unserer Methode wird die Wechselwirkung von Nachbardrähten ebenfalls berücksichtigt. Diese wird immer wichtiger, weil der Durchmesser und der wechselseitige Abstand der Bonddrähte sich verringert, wegen der fortschreitenden Miniaturisierung der Chip-Verpackungen. Unser Programm kann ebenfalls Temperaturen für transiente Ströme berechnen und den Strom berechnen, der zu einer gegebenen Maximaltemperatur gehört.
Physical analog IC design has not been automated to the same degree as digital IC design. This shortfall is primarily rooted in the analog IC design problem itself, which is considerably more complex even for small problem sizes. Significant progress has been made in analog automation in several R&D target areas in recent years. Constraint engineering and generator-based module approaches are among the innovations that have emerged. Our paper will first present a brief review of the state of the art of analog layout automation. We will then introduce active and open research areas and present two visions – a “continuous layout design flow” and a “bottom-up meets top-down design flow” – which could significantly push analog design automation towards its goal of analog synthesis.
This paper enhances SWARM, a novel deterministic analog layout automation approach based on the idea of cellular automata. SWARM implements a decentralized interaction model in which responsive layout modules, covering basic circuit types, autonomously move, rotate and deform themselves to let constraint-compliant, compact layout solutions emerge from a synergetic flow of self-organization. With the ability to consider design constraints both implicitly and explicitly, SWARM joins the layout quality of procedural generators with the flexibility of optimization algorithms, combining these two kinds of automation into a “bottom-up meets top-down” flow. The new enhancements are demonstrated in an OTA example, depicting the power of SWARM and its enormous potential for future developments.
In analog layout design, chip floorplans are usually still handcrafted by human experts. Particularly, the nondiscrete variability of block dimensions must be exploited thereby, which is a serious challenge for optimization-based algorithmic floorplanners. This paper presents a fundamentally new automation approach based on self-organization, in which floorplan blocks can autonomously move, rotate and deform themselves to jointly let compact results emerge from a synergistic flow of interaction. Our approach is able to minimize area and wirelength, supports nonslicing floorplan structures, can consider fully variable block dimensions, accounts for a fixed rectilinear boundary, and works absolutely deterministic. The approach is innovatively different from conventional, top-down oriented floorplanning algorithms.
A procedural approach to automate the manual design process in analog integrated circuit design
(2018)
This paper presents a novel approach to automating the design of analog integrated circuits: (1) the Expert Design Plan (EDP), a procedural generator, and (2) the EDP Language, a high-level description language for writing an EDP. An EDP is a parameterizable, executable script, which reproduces a designer’s course of action when designing a circuit. Thus, an EDP formalizes the design expert’s knowledge-based strategy and makes it reusable. Since it is essential that an EDP represents a circuit designers’ way of thinking and working as close as possible, the designers themselves should be enabled to create the EDP. Therefore, our approach provides a input method through a domain-specific language called EDP Language (EDPL). Using this language is intuitive and requires no special training. In an exemplary implementation of our approach, a common-source amplifier is automatically sized using a set of only 10 instructions. Even in the first usage our EDP approach has appeared to be more efficient than the manual sizing process.
In contrast to IC design, MEMS design still lacks sophisticated component libraries. Therefore, the physical design of MEMS sensors is mostly done by simply drawing polygons. Hence, the sensor structure is only given as plain graphic data which hinders the identification and investigation of topology elements such as spring, anchor, mass and electrodes. In order to solve this problem, we present a rule-based recognition algorithm which identifies the architecture and the topology elements of a MEMS sensor. In addition to graphic data, the algorithm makes use of only a few marking layers, as well as net and technology information. Our approach enables RC-extraction with commercial field solvers and a subsequent synthesis of the sensor circuit. The mapping of the extracted RC-values to the topology elements of the sensor enables a detailed analysis and optimization of actual MEMS sensors.
This paper introduces a novel placement methodology for a common-centroid (CC) pattern generator. It can be applied to various integrated circuit (IC) elements, such as transistors, capacitors, diodes, and resistors. The proposed method consists of a constructive algorithm which generates an initial, close to the optimum, solution, and an iterative algorithm which is used subsequently, if the output of constructive algorithm does not satisfy the desired criteria. The outcome of this work is an automatic CC placement algorithm for IC element arrays. Additionally, the paper presents a method for the CC arrangement evaluation. It allows for evaluating the quality of an array, and a comparison of different placement methods.
A new method for the analysis of movement dependent parasitics in full custom designed MEMS sensors
(2017)
Due to the lack of sophisticated microelectromechanical systems (MEMS) component libraries, highly optimized MEMS sensors are currently designed using a polygon driven design flow. The strength of this design flow is the accurate mechanical simulation of the polygons by finite element (FE) modal analysis. The result of the FE-modal analysis is included in the system model together with the data of the (mechanical) static electrostatic analysis. However, the system model lacks the dynamic parasitic electrostatic effects, arising from the electric coupling between the wiring and the moving structures. In order to include these effects in the system model, we present a method which enables the quasi dynamic parasitic extraction with respect to in-plane movements of the sensor structures. The method is embedded in the polygon driven MEMS design flow using standard EDA tools. In order to take the influences of the fabrication process into account, such as etching process variations, the method combines the FE-modal analysis and the fabrication process simulation data. This enables the analysis of dynamic changing electrostatic parasitic effects with respect to movements of the mechanical structures. Additionally, the result can be included into the system model allowing the simulation of positive feedback of the electrostatic parasitic effects to the mechanical structures.
We present a new methodology for automatic selection and sizing of analog circuits demonstrated on the OTA circuit class. The methodology consists of two steps: a generic topology selection method supported by a “part-sizing” process and subsequent final sizing. The circuit topologies provided by a reuse library are classified in a topology tree. The appropriate topology is selected by traversing the topology tree starting at the root node. The decision at each node is gained from the result of the part-sizing, which is in fact a node-specific set of simulations. The final sizing is a simulation-based optimization. We significantly reduce the overall simulation effort compared to a classical simulation-based optimization by combining the topology selection with the part-sizing process in the selection loop. The result is an interactive user friendly system, which eases the analog designer’s work significantly when compared to typical industrial practice in analog circuit design. The topology selection method and sizing process are implemented as a tool into a typical analog design environment. The design productivity improvement achievable by our method is shown by a comparison to other design automation approaches.
A generic, knowledge-based method for automatic topology selection of analog circuits in a predefined analog reuse library is presented in this paper on the OTA (Operational Transconductance Amplifier) example. Analog circuits of a given circuit class are classified in a topology tree, where each node represents a specific topology. Child nodes evolve from their parent nodes by an enhancement of the parent node’s topological structure. Topology selection is performed by a depth first-search in the topology tree starting at the root node, thus checking topologies of increasing complexity. The decisions at each node are based on solving equations or – if this is not possible – on simulations. The search ends at the first (and thus the simplest) topology which can meet the specification after an adequate circuit sizing. The advantages of the generic, tree based topology selection method presented in this paper are shown in comparison to a pool selection method and to heuristic approaches. The selection is based on an accomplished chip investigation.
In this paper, we address the novel EDP (Expert Design Plan) principle for procedural design automation of analog integrated circuits, which captures the knowledge-based design strategy of human circuit designers in an executable script, making it reusable. We present the EDP Player, which enables the creation and execution of EDPs for arbitrary circuits in the Cadence® Virtuoso® Design Environment. The tool provides a generic version of an instruction set, called EDPL (EDPLanguage), enabling emulation of a typical manual analog sizing flow. To automate the design of a Miller Operational Amplifier and to create variants of a Smart Power IC, several EDPs were implemented using this tool. Employing these EDPs leads to a strong reduction of design time without compromising design quality or reliability.