Automatic synthesis of analog layout : a survey

A review of recent research in the automatic synthesis of physical geometry for analog integrated circuits is presented. On introduction, an explanation of the difficulties involved in analog layout as opposed to digital layout is covered. Review of the literature then follows. Emphasis is placed on the exposition of general methods for addressing problems specific to analog layout, with the details of specific systems only being given when they surve to illustrate these methods well. The conclusion discusses problems remaining and offers a prediction as to how technology will evolve to solve them. It is argued that although progress has been and will continue to be made in the automation of analog IC layout, due to fundamental differences in the nature of analog IC design as opposed to digital design, it should not be expected that the level of automation of the former will reach that of the latter any time soon

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control

Neuro-memristive Circuits for Edge Computing: A review

The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks and open problems in the field of neuro-memristive circuits for edge computing

Geometrically-constrained, parasitic-aware synthesis of analog ICs

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

Fast, non-monte-carlo estimation of transient performance variation due to device mismatch

This paper describes an efficient way of simulating the effects of device random mismatch on circuit transient characteristics, such as variations in delay or in frequency. The proposed method models DC random offsets as equivalent AC pseudo-noises and leverages the fast, linear periodically time-varying (LPTV) noise analysis available from RF circuit simulators. Therefore, the method can be considered as an extension to DC match analysis and offers a large speed-up compared to the traditional Monte-Carlo analysis. Although the assumed linear perturbation model is valid only for small variations, it enables easy ways to estimate correlations among variations and identify the most sensitive design parameters to mismatch, all at no additional simulation cost. Three benchmarks measuring the variations in the input offset voltage of a clocked comparator, the delay of a logic path, and the frequency of an oscillator demonstrate the speed improvement of about 100-1000x compared to a 1000-point Monte-Carlo method