5,063 research outputs found

    Innovative teaching of IC design and manufacture using the Superchip platform

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    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

    Tensor Computation: A New Framework for High-Dimensional Problems in EDA

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    Many critical EDA problems suffer from the curse of dimensionality, i.e. the very fast-scaling computational burden produced by large number of parameters and/or unknown variables. This phenomenon may be caused by multiple spatial or temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit simulation), nonlinearity of devices and circuits, large number of design or optimization parameters (e.g. full-chip routing/placement and circuit sizing), or extensive process variations (e.g. variability/reliability analysis and design for manufacturability). The computational challenges generated by such high dimensional problems are generally hard to handle efficiently with traditional EDA core algorithms that are based on matrix and vector computation. This paper presents "tensor computation" as an alternative general framework for the development of efficient EDA algorithms and tools. A tensor is a high-dimensional generalization of a matrix and a vector, and is a natural choice for both storing and solving efficiently high-dimensional EDA problems. This paper gives a basic tutorial on tensors, demonstrates some recent examples of EDA applications (e.g., nonlinear circuit modeling and high-dimensional uncertainty quantification), and suggests further open EDA problems where the use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and System

    SIM-DSP: A DSP-Enhanced CAD Platform for Signal Integrity Macromodeling and Simulation

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    Macromodeling-Simulation process for signal integrity verifications has become necessary for the high speed circuit system design. This paper aims to introduce a “VLSI Signal Integrity Macromodeling and Simulation via Digital Signal Processing Techniques” framework (known as SIM-DSP framework), which applies digital signal processing techniques to facilitate the SI verification process in the pre-layout design phase. Core identification modules and peripheral (pre-/post-)processing modules have been developed and assembled to form a verification flow. In particular, a single-step discrete cosine transform truncation (DCTT) module has been developed for modeling-simulation process. In DCTT, the response modeling problem is classified as a signal compression problem, wherein the system response can be represented by a truncated set of non-pole based DCT bases, and error can be analyzed through Parseval’s theorem. Practical examples are given to show the applicability of our proposed framework

    Mixed-signal CNN array chips for image processing

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    Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) are excellent candidates for the implementation of image processing algorithms using VLSI analog parallel arrays. However, the design of general purpose, programmable CNN chips with dimensions required for practical applications raises many challenging problems to analog designers. This is basically due to the fact that large silicon area means large development cost, large spatial deviations of design parameters and low production yield. CNN designers must face different issues to keep reasonable enough accuracy level and production yield together with reasonably low development cost in their design of large CNN chips. This paper outlines some of these major issues and their solutions

    An Electromigration and Thermal Model of Power Wires for a Priori High-Level Reliability Prediction

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    In this paper, a simple power-distribution electrothermal model including the interconnect self-heating is used together with a statistical model of average and rms currents of functional blocks and a high-level model of fanout distribution and interconnect wirelength. Following the 2001 SIA roadmap projections, we are able to predict a priori that the minimum width that satisfies the electromigration constraints does not scale like the minimum metal pitch in future technology nodes. As a consequence, the percentage of chip area covered by power lines is expected to increase at the expense of wiring resources unless proper countermeasures are taken. Some possible solutions are proposed in the paper
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