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Nanoelectronic Modeling Lecture 27: NEMO1D -
09 Mar 2010 | | Contributor(s):: Gerhard Klimeck
This presentation provides a very high level software overview of NEMO1D. The items discussed are:User requirementsGraphical user interfaceSoftware structureProgram developer requirementsDynamic I/O design for batch and GUIResonance finding algorithmInhomogeneous energy meshingInformation flow,...
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Nanoelectronic Modeling Lecture 28: Introduction to Quantum Dots and Modeling Needs/Requirements
20 Jul 2010 | | Contributor(s):: Gerhard Klimeck
This presentation provides a very high level software overview of NEMO1D.Learning Objectives:This lecture provides a very high level overview of quantum dots. The main issues and questions that are addressed are:Length scale of quantum dotsDefinition of a quantum dotQuantum dot examples and...
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Nanoelectronic Modeling Lecture 29: Introduction to the NEMO3D Tool
04 Aug 2010 | | Contributor(s):: Gerhard Klimeck
This presentation provides a very high level software overview of NEMO3D. The items discussed are:Modeling Agenda and MotivationTight-Binding Motivation and basic formula expressionsTight binding representation of strainSoftware structureNEMO3D algorithm flow NEMO3D parallelization scheme –...
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Nanoelectronic Modeling: Multimillion Atom Simulations, Transport, and HPC Scaling to 23,000 Processors
07 Mar 2008 | | Contributor(s):: Gerhard Klimeck
Future field effect transistors will be on the same length scales as “esoteric” devices such as quantum dots, nanowires, ultra-scaled quantum wells, and resonant tunneling diodes. In those structures the behavior of carriers and their interaction with their environment need to be fundamentally...
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NanoElectronic MOdeling: NEMO
20 Dec 2007 | | Contributor(s):: Gerhard Klimeck
This presentation was one of 13 presentations in the one-day forum, "Excellence in Computer Simulation," which brought together a broad set of experts to reflect on the future of computational science and engineering.Novel nanoelectronic devices such as quantum dots, nanowires, and ultra-scaled...
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Nanoparticle and Colloidal Simulations with Molecular Dynamics
05 Dec 2008 | | Contributor(s):: Steve Plimpton
Modeling nanoparticle or colloidal systems in a molecular dynamics (MD) code requires coarse-graining on several levels to achieve meaningful simulation times for study of rheological and other manufacturing properties. These include treating colloids as single particles, moving from explicit to...
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NCN Cyberinfrastructure Overview
21 Jun 2005 | | Contributor(s):: Gerhard Klimeck
Presentation of the NCN cyberinfrastructure to the June 2005 NSF review team. The nanoHUB development over 12 months will be presented in a broad overview.
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NEMO 1-D: The First NEGF-based TCAD Tool and Network for Computational Nanotechnology
28 Dec 2004 | | Contributor(s):: Gerhard Klimeck
Nanotechnology has received a lot of public attention since U.S. President Clinton announced the U.S.National Nanotechnology Initiative. New approaches to applications in electronics, materials,medicine, biology and a variety of other areas will be developed in this new multi-disciplinary...
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NEMO 3D: Intel optimizations and Multiple Quantum Dot Simulations
03 Aug 2006 | | Contributor(s):: Anish Dhanekula, Gerhard Klimeck
NEMO-3D is a nanoelectronic modeling tool that analyzes the electronic structure of nanoscopic devices. Nanoelectronic devices such as Quantum Dots (QDs) can contain millions of atoms,. Therefore, simulating their electronic structure, can take up to several days. In order to simulate and analyze...
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Networked Dynamical Systems for Function and Learning: Paradigms for Data-Driven Control and Learning in Neurosensory Systems
15 Jan 2019 | | Contributor(s):: J. Nathan Kutz
Our objective is to use emerging data-driven methods to extract the underlying engineering principles of cognitive capability, namely those that allow complex networks to learn and enact control and functionality in the robust manner observed in neurosensory systems. Mathematically, the...
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New FOSLS Formulation of Nonlinear Stokes Flow for Glaciers
05 Feb 2016 | | Contributor(s):: Jeffrey Allen
This talk describes two First-order System Least-squares (FOSLS) formulations of the nonlinear Stokes flow used to model glaciers and ice sheets. The first is a Stress formulation and the second a Stress-Vorticity formulation. Both use fluidity, which is the reciprocal of viscosity and avoid the...
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Non-Blocking Conjugate Gradient Methods for Extreme Scale Computing
05 Feb 2016 | | Contributor(s):: Paul Eller
Many scientific and engineering applications use Krylov subspace methods to solve large systems of linear equations. For extreme scale parallel computing systems, the dot products in these methods (implemented using allreduce operations in MPI) can limit performance because they are a...
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Numerical Analysis
02 Jun 2006 | | Contributor(s):: Dragica Vasileska
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Numerical Aspects of NEGF: The Recursive Green Function Algorithm
14 Jun 2004 | | Contributor(s):: Gerhard Klimeck
Numerical Aspects of NEGF: The Recursive Green Function Algorithm
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OpenMP Tutorial
25 Nov 2008 | | Contributor(s):: Seung-Jai Min
This tutorial consists of three parts. First, we will discuss abouthow OpenMP is typically used and explain OpenMP programming model. Second, we will describe important OpenMP constructs and data enviroments. Finally, we will show a simple example to illustrate how OpenMP APIs are used to program...
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Overview of Computational Methods and Machine Learning: Panel Discussion
14 Jun 2019 | | Contributor(s):: Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin
The individual Panel Talks which accompanies this discussion can be found here.Why do we need experiments?Are your methods “descriptive” or “predictive”?Do you work with any other theory/simulation groups?On the 5 year timescale: is machine-learning hype or a real...
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Overview of Computational Methods and Machine Learning: Panel Talks
14 Jun 2019 | | Contributor(s):: Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin
The Panel Discussion which follows these individual presentations can be found here.Individucal Presentations:Theory and Machine Learning in the Chemical Sciences, Brett Matthew Savoie;Divide and Conquer with QM/MM Methods, Pradeep Kumar Gurunathan;Computational Chemistry/Materials, Peilin...
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Parallel Computing for Realistic Nanoelectronic Simulations
12 Sep 2005 | | Contributor(s):: Gerhard Klimeck
Typical modeling and simulation efforts directed towards the understanding of electron transport at the nanometer scale utilize single workstations as computational engines. Growing understanding of the involved physics and the need to model realistically extended devices increases the complexity...
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Parallel Multigrid Preconditioner Based on Automatic 3D Tetradedric Meshes
02 Feb 2016 | | Contributor(s):: Frederic Vi
Multigrid methods are efficient for solving large sparse linear systems. Geometric (GMG) and Algebraic Multigrid (AMG) have both their own benefits and limitations. Combining the simplicity of AMG with the efficiency of GMG lead us to the development of an Hybrid Multigrid preconditionner. From...
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PennyLane - Automatic Differentiation and Machine Learning of Quantum Computations
29 Oct 2019 | | Contributor(s):: Nathan Killoran
PennyLane is a Python-based software framework for optimization and machine learning of quantum and hybrid quantum-classical computations.