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DOE OSTI2018

Identification of the I38T PA Substitution as a Resistance Marker for Next-Generation Influenza Virus Endonuclease Inhibitors

ABSTRACT The clinical severity and annual occurrence of influenza virus epidemics, combined with the availability of just a single class of antivirals to treat infections, underscores the urgent need to develop new anti-influenza drugs. The endonuclease activity within the viral acidic polymerase (PA) protein is an attractive target for drug discovery due to the critical role it plays in viral gene transcription. RO-7 is a next-generation PA endonuclease inhibitor of influenza A and B viruses, but its drug resistance potential is unknown. Through serial passage of influenza A(H1N1) viruses in MDCK cells under selective pressure of RO-7, we identified an I38T substitution within the PA endonuclease domain that conferred in vitro resistance to RO-7 (up to a 287-fold change in 50% effective concentration [EC 50 ]). I38T emerged between 5 and 10 passages, and when introduced into recombinant influenza A(H1N1) viruses, alone conferred RO-7 resistance (up to an 81-fold change in EC 50 ). Cocrystal structures of mutant and wild-type endonuclease domains with RO-7 provided the structural basis of resistance, where a key hydrophobic interaction between RO-7 and the Ile38 side chain is compromised when mutated to the polar threonine. While Ile38 does not have a crucial role in coordinating the endonuclease active site, the switch to threonine does affect the polymerase activity of some viruses and influences RO-7 affinity for the PA N target (i.e., the ≈200-residue N-terminal domain of PA). However, the change does not lead to a complete loss of replication activity in vitro . Our results predict that RO-7-resistant influenza viruses carrying the I38T substitution may emerge under treatment. This should be taken into consideration for clinical surveillance and in refinement of these drugs. IMPORTANCE The effectiveness of antiviral drugs can be severely compromised by the emergence of resistant viruses. Therefore, determination of the mechanisms by which viruses become resistant is critical for drug development and clinical use. RO-7 is a compound that potently inhibits influenza virus replication and belongs to a new class of drugs in late-stage clinical trials for treatment of influenza virus infection. Here we demonstrate that a single amino acid change acquired under prolonged virus exposure to RO-7 renders influenza viruses significantly less susceptible to its inhibitory effects. We have discovered how the mutation can simultaneously interfere with drug activity and still maintain efficient virus replication. These findings have important implications for the development of more effective derivatives of RO-7-like drugs and provide guidance for how to monitor the emergence of resistance.

Jones, Jeremy C.↗

DOE OSTI2019

Parallel-In-Time Multigrid with Adaptive Spatial Coarsening for The Linear Advection and Inviscid Burgers Equations

We apply a multigrid reduction-in-time (MGRIT) algorithm to hyperbolic partial differential equations in one spatial dimension. This study is motivated by the observation that sequential time-stepping is a computational bottleneck when attempting to implement highly concurrent algorithms; thus parallel-in-time methods are desirable. MGRIT adds parallelism by using a hierarchy of successively coarser temporal levels to accelerate the solution on the finest level. In the case of explicit time-stepping, spatial coarsening is a suitable approach to ensure that stability conditions are satisfied on all levels, and it may be useful for implicit time-stepping by producing cheaper multigrid cycles. Unfortunately, uniform spatial coarsening results in extremely slow convergence when the wave speed is near zero, even if only locally. We present an adaptive spatial coarsening strategy that addresses this issue for the variable coefficient linear advection equation and the inviscid Burgers equation using first-order explicit or implicit time-stepping methods. Serial numerical results show this method offers significant improvements over uniform coarsening and is convergent for the inviscid Burgers equation with and without shocks. Parallel scaling tests on up to 128K cores indicate that run-time improvements over serial time-stepping strategies are possible when spatial parallelism alone saturates, and that scalability is robust for oscillatory solutions which change on the scale of the grid spacing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Abstractions and Directives for Adapting Wavefront Algorithms to Future Architectures

Architectures are rapidly evolving, and exascale machines are expected to offer billion-way concurrency. We need to rethink algorithms, languages and programming models among other components in order to migrate large scale applications and explore parallelism on these machines. Although directive-based programming models allow programmers to worry less about programming and more about science, expressing complex parallel patterns in these models can be a daunting task especially when the goal is to match the performance that the hardware platforms can offer. One such pattern is wavefront. This paper extensively studies a wavefront-based miniapplication for Denovo, a production code for nuclear reactor modeling. We parallelize the Koch-Baker-Alcouffe (KBA) parallel-wavefront sweep algorithm in the main kernel of Minisweep (the miniapplication) using CUDA, OpenMP and OpenACC. Our OpenACC implementation running on NVIDIA's next-generation Volta GPU boasts an 85.06x speedup over serial code, which is larger than CUDA's 83.72x speedup over the same serial implementation. Our experimental platform includes SummitDev, an ORNL representative architecture of the upcoming Summit supercomputer. Our parallelization effort across platforms also motivated us to define an abstract parallelism model that is architecture independent, with a goal of creating software abstractions that can be used by applications employing the wavefront sweep motif.

Searles, Robert↗

DOE OSTI2019

BCL: A Cross-Platform Distributed Data Structures Library

One-sided communication is a useful paradigm for irregular parallel applications, but most one-sided programming environments, including MPI's one-sided interface and PGAS programming languages, lack application-level libraries to support these applications. We present the Berkeley Container Library, a set of generic, cross-platform, high-performance data structures for irregular applications, including queues, hash tables, Bloom filters and more. BCL is written in C++ using an internal DSL called the BCL Core that provides one-sided communication primitives such as remote get and remote put operations. The BCL Core has backends for MPI, OpenSHMEM, GASNet-EX, and UPC++, allowing BCL data structures to be used natively in programs written using any of these programming environments. Along with our internal DSL, we present the BCL ObjectContainer abstraction, which allows BCL data structures to transparently serialize complex data types while maintaining efficiency for primitive types. We also introduce the set of BCL data structures and evaluate their performance across a number of high-performance computing systems, demonstrating that BCL programs are competitive with hand-optimized code, even while hiding many of the underlying details of message aggregation, serialization, and synchronization.

Brock, Benjamin↗

DOE OSTI2025

TorchBraid: High-Performance Layer-Parallel Training of Deep Neural Networks with MPI and GPU Acceleration

TorchBraid is a high-performance implementation of layer-parallel training for deep neural networks (DNNs) supporting MPI-based parallelism and GPU acceleration. Layer-parallel training has been developed to overcome the serialization inherent in forward and backward propagation of DNNs that limits utilization of computational resources in the strong scaling limit. To achieve this, TorchBraid integrates the PyTorch neural network framework with the state-of-the-art XBraid time-parallel library. Furthermore, this article presents the use and performance of TorchBraid, in addition to solutions for overcoming the algorithmic challenges inherent in combining automatic differentiation with layer-parallel. Results are presented with and without GPU acceleration for the Tiny ImageNet and MNIST image classification data sets, as well as recurrent neural networks. Overall, TorchBraid enables fast training of DNNs, both in a strong and weak scaling context. In addition to the TorchBraid software, several new advances in applying layer-parallel algorithms are detailed. Integration of layer-parallel with data-parallel algorithms is presented for the first time, showing the computational advantages of the combination. Standard deep learning techniques, like batch-normalization, are developed for layer-parallel training. Finally, a new approach combining layer-parallel with spatial coarsening in order to accelerate training for 3D image classification shows roughly a 10× speedup over serial execution.

Layer-parallel↗

DOE OSTI2015

MapReduceXMT v. Beta 0.1

The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming. The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming.

Goodman, Eric↗

DOE OSTI2019

MPI Stages : A Serializable MPI Library

MPI library that supports serializing (and check-pointing) its MPI Stages is a communication library that allows nodes and programs in a computer cluster to communicate via the Message-Passing Interface (MPI). The internal data objects of the library are serializable, i.e., the user can convert the MPI state or objects, such as groups or communicators, into byte streams and save them into a checkpoint file. Later users can load the checkpoint file and de-serialize previous objects into the library. Serialization/de-serialization is useful in MPI applications to recover from node failures.

Ruefenacht, Martin↗

DOE OSTI2014

Grappolo

Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains (e.g., internet, citation, biological). Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number of iterations, while providing real speedups of up to 8x using 32 threads. In addition, our parallel implementation was able to exhibit weak scaling properties on up to 32 threads.

Halappanavar, Mahantesh↗

DOE OSTI2023

Longitudinal Changes in Immune Activation Serum Biomarkers Prior to Diagnosis and Risk of B-cell NHL Subtypes

To examine the contribution of B-cell activation molecules to B-cell follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL), a prospective study was conducted using pre-diagnosis serial serum samples from the US Department of Defense Serum Repository. Each case (n = 142 FL, n = 211 DLBCL) was matched to two controls on age, gender, race, military branch, and blood collection dates. Immune activation molecules (IL1β, IL2, IL4, IL5, IL6, IL10, IL12, CXCL13, IL8, TNFα, IFNγ, GM-CSF, VEGF, sCD30, IgE) were quantified using ELISA or multiplex immunometric (Luminex) assay. Longitudinal data were analyzed using linear mixed modeling. As serial specimens were collected over several years before diagnosis, we evaluated the temporal dynamics of these markers. Increased serum levels of sCD30, CXCL13, and to a lesser extent IL10, were associated with both FL and DLBCL in cases compared with controls, with a median follow-up of 5.5 years from the earliest specimen collection to diagnosis date. Significant increasing sCD30 and CXCL13 trajectories for FL and DLBCL subtypes were noted starting at the earliest time points and with IL10 levels increasing significantly at time points closer to diagnosis. In conclusion, these results suggest that sCD30, CXCL13, and IL10 may contribute to the etiology of FL and DLBCL and are potential biomarkers for these non–Hodgkin lymphoma subtypes. The increasing trajectories of the B-cell activation molecules, sCD30, CXCL13, and to a lesser extent IL10, may indicate early disease-induced effects or reflect the chronic stimulation of B-cells that promotes the development of FL and DLBCL subtypes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

The orphan nuclear receptor EAR-2 (NR2F6) inhibits hematopoietic cell differentiation and induces myeloid dysplasia in vivo

Background: In patients with myelodysplastic syndrome (MDS), bone marrow cells have an increased predisposition to apoptosis, yet MDS cells outcompete normal bone marrow (BM)–suggesting that factors regulating growth potential may be important in MDS. We previously identified v-Erb A related-2 (EAR-2, NR2F6) as a gene involved in control of growth ability. Methods: Bone marrow obtained from C57BL/6 mice was transfected with a retrovirus containing EAR-2-IRES-GFP. Ex vivo transduced cells were flow sorted. In some experiments cells were cultured in vitro, in other experiments cells were injected into lethally irradiated recipients, along with non-transduced bone marrow cells. Short-hairpin RNA silencing EAR-2 was also introduced into bone marrow cells cultured ex vivo. Results: Here, we show that EAR-2 inhibits maturation of normal BM in vitro and in vivo and that EAR-2 transplant chimeras demonstrate key features of MDS. Competitive repopulation of lethally irradiated murine hosts with EAR2-transduced BM cells resulted in increased engraftment and increased colony formation in serial replating experiments. Recipients of EAR-2-transduced grafts had hypercellular BM, erythroid dysplasia, abnormal localization of immature precursors and increased blasts; secondary transplantation resulted in acute leukemia. Animals were cytopenic, having reduced numbers of erythrocytes, monocytes and granulocytes. Suspension culture confirmed that EAR-2 inhibits granulocytic and monocytic differentiation, while knockdown induced granulocytic differentiation. We observed a reduction in the number of BFU-E and CFU-GM colonies and the size of erythroid and myeloid colonies. Serial replating of transduced hematopoietic colonies revealed extended replating potential in EAR-2-overexpressing BM, while knockdown reduced re-plating ability. EAR-2 functions by recruitment of histone deacetylases, and inhibition of differentiation in 32D cells is dependent on the DNA binding domain. Conclusions: This data suggest that NR2F6 inhibits maturation of normal BM in vitro and in vivo and that the NR2F6 transplant chimera system demonstrates key features of MDS, and could provide a mouse model for MDS.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

SMC 2021 : Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU. RUR: This dataset is the job scheduler traces collected from the Titan supercomputerfrom 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected usingResource Utilization Report (RUR), a Cray-developed resource-usage data collectionand reporting system. It contains the usage information of its critical resources (CPU,Memory, GPU, and I/O) of each running job on Titan during that period [2]. ProjectAreas: Every job is associated with a project ID. TheProjectAreas.csvdatasetprovides a mapping of the project ID to its domain science. GPU: There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has the following fields: 1. SN : Serial number of a GPU 2. location : The location where it is installed 3. insert : The time when it was inserted into that location 4. remove : The time when it was removed from that location 5. duration : Amount of time the GPU spent in this location 6. out : If the device was taken out entirely w/o a re-installment into a new location. 7. event : If the GPU was taken out entirely, the reason for its removal. To learn more about this dataset, please refer to the git repositoryhttps://github.com/olcf/TitanGPULifeand the related publication [1]. References [1] George Ostrouchov, Don Maxwell, Rizwan A Ashraf, Christian Engelmann, MallikarjunShankar, and James H Rogers. Gpu lifetimes on titan supercomputer: Survival analysisand reliability. InSC20: International Conference for High Performance Computing,Networking, Storage and Analysis, pages 1-14. IEEE, 2020. [2] Feiyi Wang, Sarp Oral, Satyabrata Sen, and Neena Imam. Learning from five-yearresource-utilization data of titan system. In2019 IEEE International Conference onCluster Computing (CLUSTER), pages 1-6. IEEE, 2019.

42 ENGINEERING↗

DOE OSTI2015

Investigation of Yersinia pestis laboratory adaptation through a combined genomics and proteomics approach

Here, the bacterial pathogen Yersinia pestis , the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a Parallel Serial Passage Experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail , pepA , and zwf , suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS-based proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism, envelope biogenesis, iron storage and acquisition, and a type VI secretion system. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Differential laboratory passaging of SARS-CoV-2 viral stocks impacts the in vitro assessment of neutralizing antibodies

Viral populations in natural infections can have a high degree of sequence diversity, which can directly impact immune escape. However, antibody potency is often tested in vitro with a relatively clonal viral populations, such as laboratory virus or pseudotyped virus stocks, which may not accurately represent the genetic diversity of circulating viral genotypes. This can affect the validity of viral phenotype assays, such as antibody neutralization assays. To address this issue, we tested whether recombinant virus carrying SARS-CoV-2 spike (VSV-SARS-CoV-2-S) stocks could be made more genetically diverse by passage, and if a stock passaged under selective pressure was more capable of escaping monoclonal antibody (mAb) neutralization than unpassaged stock or than viral stock passaged without selective pressures. We passaged VSV-SARS-CoV-2-S four times concurrently in three cell lines and then six times with or without polyclonal antiserum selection pressure. All three of the monoclonal antibodies tested neutralized the viral population present in the unpassaged stock. The viral inoculum derived from serial passage without antiserum selection pressure was neutralized by two of the three mAbs. However, the viral inoculum derived from serial passage under antiserum selection pressure escaped neutralization by all three mAbs. Deep sequencing revealed the rapid acquisition of multiple mutations associated with antibody escape in the VSV-SARS-CoV-2-S that had been passaged in the presence of antiserum, including key mutations present in currently circulating Omicron subvariants. These data indicate that viral stock that was generated under polyclonal antiserum selection pressure better reflects the natural environment of the circulating virus and may yield more biologically relevant outcomes in phenotypic assays. Thus, mAb assessment assays that utilize a more genetically diverse, biologically relevant, virus stock may yield data that are relevant for prediction of mAb efficacy and for enhancing biosurveillance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

A Study of Successive Over-relaxation Method Parallelization over Modern HPC Languages

Successive over-relaxation (SOR) is a computationally intensive, yet extremely important iterative solver for solving linear systems. Due to recent trends of exponential growth in amount of data generated and increasing problem sizes, serial platforms have proved to be insucient in providing the required computational power. In this paper, we present parallel implementations of red-black SOR method using three modern programming languages namely Chapel, D and Go. We employ SOR method for solving 2D steady-state heat conduction problem. We discuss the optimizations incorporated and the features of these languages which are crucial for improving the program performance. Experiments have been performed using 2, 4, and 8 threads and performance results are compared with serial execution. The analysis of results provides important insights into working of SOR method.

Mittal, Sparsh↗

DOE OSTI2026

FAIRLinked: Data FAIRification Tools for Materials Data Science

FAIRLinked is a software package created to support the FAIRification of materials science data, ensuring proper alignment with FAIR principles: Findable, Accessible, Interoperable, and Reusable. It is built to be compatible with MDS-Onto, an ontology designed to capture the semantics of various types of materials data, enabling integration and sharing across different research workflows. The package is subdivided into three subpackages: InterfaceMDS, RDFTableConversion, and QBWorkflow. The first subpackage, InterfaceMDS allows users to search for terms using either string search or various filters, explore different domains and subdomains, and add terms to MDS-Onto. RDFTableConversion is used for serialization and deserialization of data from CSV into JSONLDs and vice versa in a way that captures the semantics of the data using MDS-Onto. Lastly, QBWorkflow is a serialization and deserialization workflow that incorporates RDF Data Cube vocabulary, useful for working with multidimensional datasets. By offering these packages, FAIRLinked lowers the barrier of creating FAIR, machine-actionable data for researchers in the materials science community.

FAIR↗

DOE OSTI2013

Xyce parallel electronic simulator users guide, version 6.0.

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). 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.

Keiter, Eric R↗

DOE OSTI2014

Xyce parallel electronic simulator users' guide, Version 6.0.1.

Keiter, Eric R↗

DOE OSTI2014

Xyce Parallel Electronic Simulator Users Guide Version 6.2.

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)

Keiter, Eric R.↗