Publications

Brightwell, Ronald B.

Abstract not provided.

Brightwell, Ronald B.

Abstract not provided.

Brightwell, Ronald B.

Abstract not provided.

Anzt, Hartwig A.; Loe, Jennifer A.; Rajamanickam, Sivasankaran R.

Abstract not provided.

Supercomputing Frontiers and Innovations

Bartlett, Roscoe B.; Demeshko, Irina; Gamblin, Todd; Hammond, Glenn E.; Heroux, Michael A.; Johnson, Jeffrey; Klinvex, Alicia M.; Li, Xiaoye; McInnes, Lois C.; Moulton, J.D.; Osei-Kuffuor, Daniel; Sarich, Jason; Smith, Barry; Willenbring, James M.; Yang, Ulrike M.

Extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundation for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.; Geveci, Berk G.; Pugmire, David P.; Rogers, David M.; Ma, Kwan-Liu M.; Childs, Hank C.

Abstract not provided.

Moreland, Kenneth D.; Geveci, Berk G.; Pugmire, David P.; Rogers, David M.; Ma, Kwan-Liu M.; Childs, Hank C.

Abstract not provided.

Moreland, Kenneth D.; Geveci, Berk G.; Meredith, Jeremy M.; Sewell, Chris S.; Ma, Kwan-Liu M.; Childs, Hank C.

Abstract not provided.

Moreland, Kenneth D.; Pugmire, David P.; Rogers, David M.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Meredith, Jeremy M.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Pugmire, David P.

Abstract not provided.

Moreland, Kenneth D.; Pugmire, David P.; Rogers, David M.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Meredith, Jeremy M.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Keiter, Eric R.; Verley, Jason V.; Thornquist, Heidi K.; Kuberry, Paul A.; Galvan, Edgar

Abstract not provided.

Keiter, Eric R.; Russo, Thomas V.; Schiek, Richard S.; Mei, Ting M.; Thornquist, Heidi K.; Coffey, Todd S.; Santarelli, Keith R.; Pawlowski, Roger P.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide. 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.

Hutchinson, Scott A.; Keiter, Eric R.; Hoekstra, Robert J.; Waters, Lon J.; Russo, Thomas V.; Rankin, Eric R.; Wix, Steven D.

This manual describes the use of the Xyce Parallel Electronic Simulator code for simulating electrical circuits at a variety of abstraction levels. The Xyce Parallel Electronic Simulator has been written to support,in a rigorous manner, the simulation needs of the Sandia National Laboratories electrical designers. As such, the development has focused on improving the capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. (3) A client-server or multi-tiered operating model wherein the numerical kernel can operate independently of the graphical user interface (GUI). (4) Object-oriented code design and implementation using modern coding-practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. The code is a parallel code in the most general sense of the phrase--a message passing parallel implementation--which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Furthermore, careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved even as the number of processors grows. Another feature required by designers is the ability to add device models, many specific to the needs of Sandia, to the code. To this end, the device package in the Xyce Parallel Electronic Simulator is designed to support a variety of device model inputs. These input formats include standard analytical models, behavioral models and look-up tables. Combined with this flexible interface is an architectural design that greatly simplifies the addition of circuit models. One of the most important contribution Xyce makes to the designers at Sandia National Laboratories is in providing a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia now has an ''in-house''capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods) research and development can be performed. Furthermore, these capabilities will then be migrated to the end users.

Hutchinson, Scott A.; Keiter, Eric R.; Hoekstra, Robert J.; Russo, Thomas V.; Rankin, Eric R.; Pawlowski, Roger P.; Fixel, Deborah A.; Schiek, Richard S.; Bogdan, Carolyn W.

This manual describes the use of theXyceParallel Electronic Simulator.Xycehasbeen designed as a SPICE-compatible, high-performance analog circuit simulator, andhas been written to support the simulation needs of the Sandia National Laboratorieselectrical designers. This development has focused on improving capability over thecurrent state-of-the-art in the following areas:%04Capability to solve extremely large circuit problems by supporting large-scale par-allel computing platforms (up to thousands of processors). Note that this includessupport for most popular parallel and serial computers.%04Improved performance for all numerical kernels (e.g., time integrator, nonlinearand linear solvers) through state-of-the-art algorithms and novel techniques.%04Device models which are specifically tailored to meet Sandia's needs, includingmany radiation-aware devices.3 XyceTMUsers' Guide%04Object-oriented code design and implementation using modern coding practicesthat ensure that theXyceParallel Electronic Simulator will be maintainable andextensible far into the future.Xyceis a parallel code in the most general sense of the phrase - a message passingparallel implementation - which allows it to run efficiently on the widest possible numberof computing platforms. These include serial, shared-memory and distributed-memoryparallel as well as heterogeneous platforms. Careful attention has been paid to thespecific nature of circuit-simulation problems to ensure that optimal parallel efficiencyis achieved as the number of processors grows.The development ofXyceprovides a platform for computational research and de-velopment aimed specifically at the needs of the Laboratory. WithXyce, Sandia hasan %22in-house%22 capability with which both new electrical (e.g., device model develop-ment) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms)research and development can be performed. As a result,Xyceis a unique electricalsimulation capability, designed to meet the unique needs of the laboratory.4 XyceTMUsers' GuideAcknowledgementsThe authors would like to acknowledge the entire Sandia National Laboratories HPEMS(High Performance Electrical Modeling and Simulation) team, including Steve Wix, CarolynBogdan, Regina Schells, Ken Marx, Steve Brandon and Bill Ballard, for their support onthis project. We also appreciate very much the work of Jim Emery, Becky Arnold and MikeWilliamson for the help in reviewing this document.Lastly, a very special thanks to Hue Lai for typesetting this document with LATEX.TrademarksThe information herein is subject to change without notice.Copyrightc 2002-2003 Sandia Corporation. All rights reserved.XyceTMElectronic Simulator andXyceTMtrademarks of Sandia Corporation.Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence DesignSystems, Inc.Silicon Graphics, the Silicon Graphics logo and IRIX are registered trademarks of SiliconGraphics, Inc.Microsoft, Windows and Windows 2000 are registered trademark of Microsoft Corporation.Solaris and UltraSPARC are registered trademarks of Sun Microsystems Corporation.Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation.HP and Alpha are registered trademarks of Hewlett-Packard company.Amtec and TecPlot are trademarks of Amtec Engineering, Inc.Xyce's expression library is based on that inside Spice 3F5 developed by the EECS De-partment at the University of California.All other trademarks are property of their respective owners.ContactsBug Reportshttp://tvrusso.sandia.gov/bugzillaEmailxyce-support%40sandia.govWorld Wide Webhttp://www.cs.sandia.gov/xyce5 XyceTMUsers' GuideThis page is left intentionally blank6

Keiter, Eric R.; Warrender, Christina E.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide. 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. The Xyce Parallel Electronic Simulator has been written to support, in a rigorous manner, the simulation needs of the Sandia National Laboratories electrical designers. It is targeted specifically to run on large-scale parallel computing platforms but also runs well on a variety of architectures including single processor workstations. It also aims to support a variety of devices and models specific to Sandia needs. This document is intended to complement the Xyce Users Guide. It contains comprehensive, detailed information about a number of topics pertinent to the usage of Xyce. Included in this document is a netlist reference for the input-file commands and elements supported within Xyce; a command line reference, which describes the available command line arguments for Xyce; and quick-references for users of other circuit codes, such as Orcad's PSpice and Sandia's ChileSPICE.

Keiter, Eric R.; Warrender, Christina E.; Verley, Jason V.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

Abstract not provided.

Keiter, Eric R.; Hutchinson, Scott A.; Hoekstra, Robert J.; Russo, Thomas V.; Rankin, Eric R.; Pawlowski, Roger P.; Fixel, Deborah A.; Wix, Steven D.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users' Guide. 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.

Keiter, Eric R.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide. 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.

Keiter, Eric R.; Warrender, Christina E.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

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: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers; (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. (3) Device models which are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only); and (4) Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful 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. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory.

Keiter, Eric R.; Warrender, Christina E.; Verley, Jason V.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

Abstract not provided.

Keiter, Eric R.; Hutchinson, Scott A.; Hoekstra, Robert J.; Russo, Thomas V.; Rankin, Eric R.; Pawlowski, Roger P.; Wix, Steven D.; Fixel, Deborah A.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator capable of simulating electrical circuits at a variety of abstraction levels. Primarily, Xyce has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability the current state-of-the-art in the following areas: {sm_bullet} Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. {sm_bullet} Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. {sm_bullet} Device models which are specifically tailored to meet Sandia's needs, including many radiation-aware devices. {sm_bullet} A client-server or multi-tiered operating model wherein the numerical kernel can operate independently of the graphical user interface (GUI). {sm_bullet} Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing of computing platforms. These include serial, shared-memory and distributed-memory parallel implementation - which allows it to run efficiently on the widest possible number parallel as well as heterogeneous platforms. Careful 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. One feature required by designers is the ability to add device models, many specific to the needs of Sandia, to the code. To this end, the device package in the Xyce These input formats include standard analytical models, behavioral models look-up Parallel Electronic Simulator is designed to support a variety of device model inputs. tables, and mesh-level PDE device models. Combined with this flexible interface is an architectural design that greatly simplifies the addition of circuit models. One of the most important feature of Xyce is in providing a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia now has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods) research and development can be performed. Ultimately, these capabilities are migrated to end users.

Keiter, Eric R.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

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: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. (3) Device models which are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only). (4) Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful 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. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory.

Keiter, Eric R.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

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: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. (3) Device models which are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only). (4) Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful 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. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory.

Keiter, Eric R.; Hutchinson, Scott A.; Hoekstra, Robert J.; Russo, Thomas V.

This document is intended to contain a detailed description of the mathematical formulation of Xyce, a massively parallel SPICE-style circuit simulator developed at Sandia National Laboratories. The target audience of this document are people in the role of 'service provider'. An example of such a person would be a linear solver expert who is spending a small fraction of his time developing solver algorithms for Xyce. Such a person probably is not an expert in circuit simulation, and would benefit from an description of the equations solved by Xyce. In this document, modified nodal analysis (MNA) is described in detail, with a number of examples. Issues that are unique to circuit simulation, such as voltage limiting, are also described in detail.

Keiter, Eric R.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Coffey, Todd S.; Thornquist, Heidi K.; Verley, Jason V.; Warrender, Christina E.

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] .

Keiter, Eric R.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Coffey, Todd S.; Thornquist, Heidi K.; Verley, Jason V.; Warrender, Christina E.

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] .

Keiter, Eric R.; Santarelli, Keith R.; Hoekstra, Robert J.; Russo, Thomas V.; Schiek, Richard S.; Mei, Ting M.; Thornquist, Heidi K.; Pawlowski, Roger P.; Coffey, Todd S.

The Xyce Parallel Electronic Simulator has been written to support, in a rigorous manner, the simulation needs of the Sandia National Laboratories electrical designers. Specific requirements include, among others, the ability to solve extremely large circuit problems by supporting large-scale parallel computing platforms, improved numerical performance and object-oriented code design and implementation. The Xyce release notes describe: Hardware and software requirements New features and enhancements Any defects fixed since the last release Current known defects and defect workarounds For up-to-date information not available at the time these notes were produced, please visit the Xyce web page at http://www.cs.sandia.gov/xyce.

Keiter, Eric R.; Warrender, Christina E.; Mei, Ting M.; Russo, Thomas V.; Schiek, Richard S.; Thornquist, Heidi K.; Verley, Jason V.; Coffey, Todd S.; Pawlowski, Roger P.

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.

Russo, Thomas V.; Mei, Ting M.; Keiter, Eric R.; Schiek, Richard S.; Thornquist, Heidi K.; Verley, Jason V.; Coffey, Todd S.; Pawlowski, Roger P.; Warrender, Christina E.

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.

Kuberry, Paul A.; Mei, Ting M.; Keiter, Eric R.; Paskaleva, Biliana S.; Bochev, Pavel B.; Hanson, Joshua M.

Abstract not provided.

Keiter, Eric R.; Mei, Ting M.; Russo, Thomas V.; Pawlowski, Roger P.; Schiek, Richard S.; Santarelli, Keith R.; Coffey, Todd S.; Thornquist, Heidi K.

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users’ Guide. 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.

Kogge, Peter M.; Resnick, David R.

The HPC architectures of today are significantly different for a decade ago, with high odds that further changes will occur on the road to Exascale. This report discusses the "perfect stora' in technology that produced this change, the classes of architectures we are dealing with, and probable trends in how they will evolve. These properties and trends are then evaluated in terms of what it likely means to future Exascale systems and applications. This page intentionally left blank.

Dornburg, Courtney S.; Davidson, George S.; Forsythe, James C.

A web-based brainstorm was conducted in the summer of 2007 within the Sandia Restricted Network. This brainstorming experiment was modeled around the 'yellow sticky' brainstorms that are used in many face-to-face meetings at Sandia National Laboratories. This document discusses the implementation and makes suggestions for future implementations.

Oldfield, Ron A.

Abstract not provided.

Dunlavy, Daniel D.; Basilico, Justin D.; Verzi, Stephen J.; Bauer, Travis L.

This report describes the Licensing Support Network (LSN) Assistant--a set of tools for categorizing e-mail messages and documents, and investigating and correcting existing archives of categorized e-mail messages and documents. The two main tools in the LSN Assistant are the LSN Archive Assistant (LSNAA) tool for recategorizing manually labeled e-mail messages and documents and the LSN Realtime Assistant (LSNRA) tool for categorizing new e-mail messages and documents. This report focuses on the LSNAA tool. There are two main components of the LSNAA tool. The first is the Sandia Categorization Framework, which is responsible for providing categorizations for documents in an archive and storing them in an appropriate Categorization Database. The second is the actual user interface, which primarily interacts with the Categorization Database, providing a way for finding and correcting categorizations errors in the database. A procedure for applying the LSNAA tool and an example use case of the LSNAA tool applied to a set of e-mail messages are provided. Performance results of the categorization model designed for this example use case are presented.

Lopez, Oscar L.; Lehoucq, Richard B.; Dunlavy, Daniel D.

We propose a novel statistical inference paradigm for zero-inflated multiway count data that dispenses with the need to distinguish between true and false zero counts. Our approach ignores all zero entries and applies zero-truncated Poisson regression on the positive counts. Inference is accomplished via tensor completion that imposes low-rank structure on the Poisson parameter space. Our main result shows that an $\textit{N}$-way rank-R parametric tensor 𝓜 ϵ (0, ∞)^{$I$Χ∙∙∙Χ$I$} generating Poisson observations can be accurately estimated from approximately $IR^2 \text{log}^2_2(I)$ non-zero counts for a nonnegative canonical polyadic decomposition. Several numerical experiments are presented demonstrating that our zero-truncated paradigm is comparable to the ideal scenario where the locations of false zero counts are known $\textit{a priori}$.

Boman, Erik G.; Devine, Karen D.

Abstract not provided.

Boman, Erik G.; Devine, Karen D.; Riesen, Lee A.; Heaphy, Robert T.; Hendrickson, Bruce A.; Vaughan, Courtenay T.

Abstract not provided.

Devine, Karen D.; Rajamanickam, Sivasankaran R.; Prokopenko, Andrey V.; Boman, Erik G.

Abstract not provided.

Wolf, Michael W.

The objectives of this presentation are: (1) Learn how to partition a problem using Zoltan; (2) Understand the following (a) Basic process of partitioning with Zoltan, (b) Setting Zoltan parameters, (c) Registering query functions, (d) Writing query functions, (e) Zoltan-LB-Partition and its input/output; and (3) Be able to integrate Zoltan into your own applications.

Wolf, Michael W.

Abstract not provided.

Boman, Erik G.; Devine, Karen D.; Leung, Vitus J.; Rajamanickam, Sivasankaran R.

Abstract not provided.