9,845 research outputs found

    Geometrically-constrained, parasitic-aware synthesis of analog ICs

    Get PDF
    In order to speed up the design process of analog ICs, iterations between different design stages should be avoided as much as possible. More specifically, spins between electrical and physical synthesis should be reduced for this is a very time-consuming task: if circuit performance including layout-induced degradations proves unacceptable, a re-design cycle must be entered, and electrical, physical, or both synthesis processes, would have to be repeated. It is also worth noting that if geometric optimization (e.g., area minimization) is undertaken after electrical synthesis, it may add up as another source of unexpected degradation of the circuit performance due to the impact of the geometric variables (e.g., transistor folds) on the device and the routing parasitic values. This awkward scenario is caused by the complete separation of said electrical and physical synthesis, a design practice commonly followed so far. Parasitic-aware synthesis, consisting in including parasitic estimates to the circuit netlist directly during electrical synthesis, has been proposed as solution. While most of the reported contributions either tackle parasitic-aware synthesis without paying special attention to geometric optimization or approach both issues only partially, this paper addresses the problem in a unified way. In what has been called layout-aware electrical synthesis, a simulation-based optimization algorithm explores the design space with geometric variables constrained to meet certain user-defined goals, which provides reliable estimates of layout-induced parasitics at each iteration, and, thereby, accurate evaluation of the circuit ultimate performance. This technique, demonstrated here through several design examples, requires knowing layout details beforehand; to facilitate this, procedural layout generation is used as physical synthesis approach due to its rapidness and ability to capture analog layout know-how.Ministerio de Educación y Ciencia TEC2004-0175

    CMOS design of chaotic oscillators using state variables: a monolithic Chua's circuit

    Get PDF
    This paper presents design considerations for monolithic implementation of piecewise-linear (PWL) dynamic systems in CMOS technology. Starting from a review of available CMOS circuit primitives and their respective merits and drawbacks, the paper proposes a synthesis approach for PWL dynamic systems, based on state-variable methods, and identifies the associated analog operators. The GmC approach, combining quasi-linear VCCS's, PWL VCCS's, and capacitors is then explored regarding the implementation of these operators. CMOS basic building blocks for the realization of the quasi-linear VCCS's and PWL VCCS's are presented and applied to design a Chua's circuit IC. The influence of GmC parasitics on the performance of dynamic PWL systems is illustrated through this example. Measured chaotic attractors from a Chua's circuit prototype are given. The prototype has been fabricated in a 2.4- mu m double-poly n-well CMOS technology, and occupies 0.35 mm/sup 2/, with a power consumption of 1.6 mW for a +or-2.5-V symmetric supply. Measurements show bifurcation toward a double-scroll Chua's attractor by changing a bias current

    Innovative teaching of IC design and manufacture using the Superchip platform

    No full text
    In this paper we describe how an intelligent chip architecture has allowed a large cohort of undergraduate students to be given effective practical insight into IC design by designing and manufacturing their own ICs. To achieve this, an efficient chip architecture, the “Superchip”, has been developed, which allows multiple student designs to be fabricated on a single IC, and encapsulated in a standard package without excessive cost in terms of time or resources. We demonstrate how the practical process has been tightly coupled with theoretical aspects of the degree course and how transferable skills are incorporated into the design exercise. Furthermore, the students are introduced at an early stage to the key concepts of team working, exposure to real deadlines and collaborative report writing. This paper provides details of the teaching rationale, design exercise overview, design process, chip architecture and test regime

    Generalized disjunction decomposition for evolvable hardware

    Get PDF
    Evolvable hardware (EHW) refers to self-reconfiguration hardware design, where the configuration is under the control of an evolutionary algorithm (EA). One of the main difficulties in using EHW to solve real-world problems is scalability, which limits the size of the circuit that may be evolved. This paper outlines a new type of decomposition strategy for EHW, the “generalized disjunction decomposition” (GDD), which allows the evolution of large circuits. The proposed method has been extensively tested, not only with multipliers and parity bit problems traditionally used in the EHW community, but also with logic circuits taken from the Microelectronics Center of North Carolina (MCNC) benchmark library and randomly generated circuits. In order to achieve statistically relevant results, each analyzed logic circuit has been evolved 100 times, and the average of these results is presented and compared with other EHW techniques. This approach is necessary because of the probabilistic nature of EA; the same logic circuit may not be solved in the same way if tested several times. The proposed method has been examined in an extrinsic EHW system using the(1+lambda)(1 + lambda)evolution strategy. The results obtained demonstrate that GDD significantly improves the evolution of logic circuits in terms of the number of generations, reduces computational time as it is able to reduce the required time for a single iteration of the EA, and enables the evolution of larger circuits never before evolved. In addition to the proposed method, a short overview of EHW systems together with the most recent applications in electrical circuit design is provided

    Configurable 3D-integrated focal-plane sensor-processor array architecture

    Get PDF
    A mixed-signal Cellular Visual Microprocessor architecture with digital processors is described. An ASIC implementation is also demonstrated. The architecture is composed of a regular sensor readout circuit array, prepared for 3D face-to-face type integration, and one or several cascaded array of mainly identical (SIMD) processing elements. The individual array elements derived from the same general HDL description and could be of different in size, aspect ratio, and computing resources

    Neuro-fuzzy chip to handle complex tasks with analog performance

    Get PDF
    This paper presents a mixed-signal neuro-fuzzy controller chip which, in terms of power consumption, input–output delay, and precision, performs as a fully analog implementation. However, it has much larger complexity than its purely analog counterparts. This combination of performance and complexity is achieved through the use of a mixed-signal architecture consisting of a programmable analog core of reduced complexity, and a strategy, and the associated mixed-signal circuitry, to cover the whole input space through the dynamic programming of this core. Since errors and delays are proportional to the reduced number of fuzzy rules included in the analog core, they are much smaller than in the case where the whole rule set is implemented by analog circuitry. Also, the area and the power consumption of the new architecture are smaller than those of its purely analog counterparts simply because most rules are implemented through programming. The Paper presents a set of building blocks associated to this architecture, and gives results for an exemplary prototype. This prototype, called multiplexing fuzzy controller (MFCON), has been realized in a CMOS 0.7 um standard technology. It has two inputs, implements 64 rules, and features 500 ns of input to output delay with 16-mW of power consumption. Results from the chip in a control application with a dc motor are also provided

    Neuro-fuzzy chip to handle complex tasks with analog performance

    Get PDF
    This Paper presents a mixed-signal neuro-fuzzy controller chip which, in terms of power consumption, input-output delay and precision performs as a fully analog implementation. However, it has much larger complexity than its purely analog counterparts. This combination of performance and complexity is achieved through the use of a mixed-signal architecture consisting of a programmable analog core of reduced complexity, and a strategy, and the associated mixed-signal circuitry, to cover the whole input space through the dynamic programming of this core [1]. Since errors and delays are proportional to the reduced number of fuzzy rules included in the analog core, they are much smaller than in the case where the whole rule set is implemented by analog circuitry. Also, the area and the power consumption of the new architecture are smaller than those of its purely analog counterparts simply because most rules are implemented through programming. The Paper presents a set of building blocks associated to this architecture, and gives results for an exemplary prototype. This prototype, called MFCON, has been realized in a CMOS 0.7μm standard technology. It has two inputs, implements 64 rules and features 500ns of input to output delay with 16mW of power consumption. Results from the chip in a control application with a DC motor are also provided
    corecore