Publications

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This report summarizes the work done in the first year of LDRD 2014-0788, titled "Advanced Uncertainty Quantification Methods for Circuit Simulation." This is a working report, created to document the methods and algorithms we investigated during the first year of this LDRD.

Sensing and calculating electronic systems with stringent accuracy requirements use internal standard voltages for references. Conceptually, this is related to using some unit measurement for counting any quantity. The high precision electronic components used in systems in the nation’s stockpile also make use of these standard voltages. The need for stable voltage references has been long-standing in the overall electronics industry. For many applications, the most pressing need is for stability of a reference voltage as the circuit temperature varies. Typical circuit components have temperature coefficients for their operational characteristics that are given in some delta per degree centigrade and these coefficients can be either positive or negative. Thus, it is natural to consider building a circuit out of components that have complementary temperature coefficients so that the operating characteristics of the circuit have a net zero temperature coefficient. This is the fundamental basis of precision voltage reference (PVR) circuit operation and it is straightforward to extend this type of stabilization to reduce shifts caused by hostile environment radiation.

This writeup is intended to address some questions about the compact model for neutron effects in HBT's that came up during the QASPR independent review.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been de- signed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. Trademarks The information herein is subject to change without notice. Copyright c 2002-2014 Sandia Corporation. All rights reserved. Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Portions of the Xyce TM code are: Copyright c 2002, The Regents of the University of California. Produced at the Lawrence Livermore National Laboratory. Written by Alan Hindmarsh, Allan Taylor, Radu Serban. UCRL-CODE-2002-59 All rights reserved. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. Xyce 's expression library is based on that inside Spice 3F5 developed by the EECS Department at the University of California. The EKV3 MOSFET model was developed by the EKV Team of the Electronics Laboratory-TUC of the Technical University of Crete. All other trademarks are property of their respective owners. Contacts Bug Reports (Sandia only) http://joseki.sandia.gov/bugzilla http://charleston.sandia.gov/bugzilla World Wide Web http://xyce.sandia.gov http://charleston.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only)

The highlights of the Xyce 6.1 release are documented.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas; Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers; A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models; Device models that are specifically tailored to meet Sandia's needs, including some radiationaware devices (for Sandia users only); and Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase-a message passing parallel implementation-which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users<U+2019> Guide [1] . The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce Users<U+2019> Guide [1] .

Abstract not provided.

The highlights of the Xyce 6.0.1 release are documented.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandias needs, including some radiationaware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase a message passing parallel implementation which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide [1] . The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce Users Guide [1] .

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While Xyce uses the Autoconf and Automake system to configure builds, it is often necessary to perform more than the customary %E2%80%9C./configure%E2%80%9D builds many open source users have come to expect. This document describes the steps needed to get Xyce built on a number of common platforms.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandias needs, including some radiationaware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase a message passing parallel implementation which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide [1] . The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce Users Guide [1] .

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Photocurrent generated by ionizing radiation represents a threat to microelectronics in radiation environments. Circuit simulation tools such as SPICE [1] can be used to analyze these threats, and typically rely on compact models for individual electrical components such as transistors and diodes. Compact models consist of a handful of differential and/or algebraic equations, and are derived by making simplifying assumptions to any of the many semiconductor transport equations. Historically, many photocurrent compact models have suffered from accuracy issues due to the use of qualitative approximation, rather than mathematically correct solutions to the ambipolar diffusion equation. A practical consequence of this inaccuracy is that a given model calibration is trustworthy over only a narrow range of operating conditions. This report describes work to produce improved compact models for photocurrent. Specifically, an analytic model is developed for epitaxial diode structures that have a highly doped subcollector. The analytic model is compared with both numerical TCAD calculations, as well as the compact model described in reference [2]. The new analytic model compares well against TCAD over a wide range of operating conditions, and is shown to be superior to the compact model from reference [2].

Many subsystems encountered in communication systems can be modeled as linear periodic time-varyiing (LPTV) systems. In this paper, we present a novel structure preserving reduced-order modeling algorithm for LPTV systems. A key advance of our approach is that it preserves the periodic time-varying structure during the reduction process, thus resulting in reduced LPTV systems. Unlike prior LPTV model order reduction (MOR) techniques which recast the LPTV systems to artificial linear time-invariant (LTI) systems and apply LTI MOR techniques for reduction, our structure preserving algorithm uses a time-varying projection directly on the original LPTV systems. Our approach always produces a smaller system than the original system, which was not valid for previous LPTV MOR techniques. We validate the proposed technique with several circuit examples, demonstrating significant size reductions and excellent accuracy. © 2011 IEEE.