Courses
LASiGMA provides an education plan that includes new materials science graduate courses delivered across the State. A core set of interinstitutional graduate level courses (three in the first year, six more in subsequent years) in computational science, multiscale modeling methods, advanced experimental techniques, and other topics are being developed and broadcast throughout the State using synchronous HD video as well as asynchronous methods. These courses will be integrated into existing and new graduate curricula on each campus, providing graduate students a transformative educational experience in materials science, who who will enter the workforce as highlyskilled, welltrained computational materials scientists.
If your LASiGMA institution is interested in offering these courses to your students, please contact Juana Moreno at moreno AT lsu.edu
For Spring 2015, the following courses will be offered
 GPU Microarchitecture, David Koppelman, M W F 11:30 a.m.12:20 p.m. (LSU course EE 7722)
 Many Body Theory, Mark Jarrell, M W F 9:3010:20 a.m. (LSU course PHYS 7893)
 Condensed Matter Physics, Ilya Vekhter, M W F 10:3011:20 a.m. (LSU course PHYS 7364)
If you are a LSU student interested in these courses, please register early to ensure the course meets the required minimum student enrollment. Students at other universities, please contact Juana Moreno at moreno AT lsu.edu as soon as possible to arrange for the course to be offered at your university. Postdocs can attend without registering but we ask you to notify us. Classes begin January 14th and end May 2nd.

GPU Microarchitecture

Taught by: David Koppelman (LSU)
Teaching periods: Spring 2015, Spring 2014This graduate course is taught by David Koppelman. This course will start with an overview of accelerators (e.g., NVIDIA GPUs, Xeon Phi) and a survey of APIs (CUDA, OpenCL, OpenMP, OpenACC). It will continue with a discussion of parallelism (threads, latency, performance limiters), CPU execution features (dynamic scheduling, caches, branch prediction), execution architecture (manythread (NVIDIA GPU) vs. manycore (Xeon Phi) organization, functional units, scheduling), storage hierarchy and synchronization (address spaces, scratchpad stores and cache, basic data access and reduction strategies), instruction sets, basic algorithms (matrix multiplication, reduction, stencil calculations, sorting), and new research directions in heterogeneous computing.
2015 classes meet Monday, Wednesday, and Friday 11:30a.m.  12:20p.m. For more information and course materials, please visit http://www.ece.lsu.edu/koppel/gp/ or contact David Koppelman at "koppel AT ece.lsu.edu"


Computational Solid State Physics

Taught by: Rongying Jin (LSU) and Cyrill Slezak (Hillsdale College, Michigan)
Teaching periods: Fall 2010Lecture 1, lecture 2, lecture 3, lecture 4, lecture 5, lecture 6, lecture 7a, lecture 7b, lecture 8, lecture 9a, lecture 9b, lecture 10, lecture 11, lecture 12, lecture 13, lecture 14, lecture 15, lecture 16, lecture 17, lecture 18, lecture 19, lecture 20a, lecture 20b, lecture 21, lecture 22a, lecture 22b, lecture 23, lecture 24
For more information and course materials, please contact Rongying Jin at rjin AT lsu.edu


Many Body Theory

Taught by: Mark Jarrell (LSU)
Teaching periods: Spring 2015, Spring 2014, Spring 2013, Spring 2012, Spring 2011This graduate course focuses on advanced manybody techniques in material science, and is taught by Mark Jarrell. If students are interested, the first month of the course is dedicated to discuss advanced statistical mechanics, including the physics of phase transitions (scale invariance near the critical point, scaling, renormalization group, etc). The rest of the course focuses in many body theory either using a conventional approach (GellmanLow, Wick's theory) or a pathintegral based approach. Nonequilibrium Green function formalism, the Keldysh formalism, or even the Wagner formalism could be also discussed. In addition, several manybody numerical methods are derived and used in class projects, including Dynamical Mean Field Approximation, Dynamical Cluster Approximation and renormalization group. A basic course in Condensed Matter/Solid State Physics (Ashcroft/Mermin) is a suggested prerequisite for this course. 2015 classes meet Monday, Wednesday, and Friday 9:3010:20 a.m.
For additional information, and course materials, please contact Mark Jarrell at jarrellphysicsatgmail.com
Course materials can be found at
http://www.phys.lsu.edu/~jarrell/TEACH.html, which includes the courses Solid State Physics, Advanced Solid State Physics, and Computational Methods in Many Body Theory


Introduction to Statistical Thermodynamics

Taught by: Randall Hall (LSU)
Teaching periods: Fall 2011Statistical Thermodynamics is a upper level undergraduate course. The focus of the course is on introductory quantum and classical statistical thermodynamics of some simple systems of chemical relevance. This course introduces students to statistical mechanics and modern simulation methods. Students from chemistry, physics, mechanical and chemical engineering, and mathematics are likely to find this of interest. To coordinate with the La Tech quarter system, we hold 2 hour lectures twice a week over a tenweek period.
For additional information and course materials, please contact Randall Hall at randall.hall AT dominican.edu
Videos of the recorded lectures can be accessed here.


Molecular Dynamics

Taught by: Tom Bishop and Collin Wick (LATech), Michal Brylinski and Dorel Moldovan (LSU) and Steve Rick (UNO)
Teaching periods: Spring 2013Molecular Dynamics is a threecredit graduate course, taught by a team of faculty including Tom Bishop and Collin Wick (Louisiana Tech), Michal Brylinski and Dorel Moldovan (LSU), and Steve Rick (Univ. of New Orleans). The course is an introduction to mastering the art of molecular modeling and dynamics simulations with an emphasis on high performance computing and modeling biomolecular systems. It will be team taught and meet once a week for video lectures. Each student will conduct a molecular simulation project. Students who take this course will learn how to configure a computer cluster (ideally a Little Fe but any two computers and a network switch can be used), install and utilize freely available molecular visualization, analysis and dynamics software tools, construct systems and run simulations on local and remote computing resources. Course work and lectures will cover essential structural biology and theoretical considerations from basic numerical integration techniques (e.g. Verlet algorithm, Ewald summations) to advanced thermodynamic considerations (e.g. replica exchange and free energy calculations). Projects are designed to explore an important biological application, a proper use of an advanced simulation technique, or performance characterization (e.g. numeric and performance analysis of GPU vs. traditional CPU). The schedule of the class have not been decided yet. For additional information and course materials, or if you are interested in registering for this course, please contact Thomas Bishop at bishopatlatech.edu.
Course materials can be found at
http://dna.engr.latech.edu/~bishop/Teaching/LASiGMAMD/.


Programming Techniques for Scientific Simulations: C++ Scientific libraries

Taught by: Matthias Troyer (ETHZurich)
Teaching periods: Fall 2010, Fall 2012, Fall 2013This lecture provides an overview of programming techniques for scientific simulations. The focus is on advances C++ programming techniques and scientific software libraries. Based on an overview over the hardware components of PCs and supercomputer, optimization methods for scientific simulation codes are explained.
For more information and course materials, please visit http://www.itp.phys.ethz.ch/education/hs10/pt or contact Matthias Troyer at matthias.troyer AT itp.phys.ethz.ch


3D+ Visualization: Avizo, VisIt, and Mathematica

Taught by: Les Butler (LSU) and Jinghua Ge (LSU)
Teaching periods: Spring 2012.This course is intended for chemists, biologists, materials scientist, anthropologists, engineers, physicists, and computer scientists. We will use workstations, your laptops, and a highperformance computer cluster to visualize 3D+ data sets. The data sets are usually of tangible objects: rocks, polymers, microfabricated devices, sharks, alligators, human cadavers1, or objects you image with a benchtop tomography instrument2. The goal is to understand how tomography data are acquired, transformed into 3D data sets, visualized, and interpreted. You will make movies of your data sets.
Topics to be discussed include:
• Tomography: Xray, Beer’s law, Kedge, sinogram, inverse Radon, interferometry
• Data sets: Binary, HDF5, stacked TIFF, DICOM
• Software: ImageJ3 on your laptop, Avizo in the lab, VisIt and VisTrails on HPC Melete
• Visualization: Binarization, distance and watershed transformations, morphological component analysis, affine transformations
• Movie making: Avizo and VisIt
• Computation: Run prewritten Mathematica on your laptop and HPC Melete. This is not a programming course.
For additional information and course materials, such as data files, please contact Les Butler at lbutler AT lsu.eduLecture 1: Introduction
Lecture 2: ImageJ  binary and HDF5 files
Lecture 3: Mathematica  binary and HDF5 files
Lecture 4: Erosion, dilation, and label fields
Lecture 5: Workflows, manipulate, and transforms (distance, gradient, watershed)
Lecture 6: Manipulate, Orthoslice viewer
Lecture 7: Function, manipulate, Orthoslice viewer
Lecture 8: Homeworks 4 and 5
Lecture 9: Component list
Lecture 10: Segmentation  Part 1
Lecture 11: Segmentation  Part 2
Lecture 12: Segmentation  Part 3
Lecture 13: Segmentation  Part 4
Lecture 14: Affine transformations, LLNL VisIt
Lecture 15: LLNL VisIt data import
Lecture 16a: VisIt  HPC Batch
Lecture 16b: VisIt  HPC Example
Lecture 17: VisIt  HPC Batch version 2, movies
Lecture 19: Independent projects
Lecture 20: VisIt camera orbit


Computational Biology: from sequence to structure to function

Taught by: Michal Brylinksi (LSU)
Teaching periods: Spring 2014This is a graduate course taught by Michal Brylinksi. It will focus on computational techniques broadly used in biological sciences to support experimental research. It will cover current methods for the modeling of protein structure and molecular function from genomic data, with emphasis placed on principles and methods commonly used in structurebased drug design. The strengths and limitations of divers molecular modeling strategies will be discussed. Students are expected to be able to apply many of the covered modeling techniques to their research.
2014 classes will meet on Tuesdays and Thursdays 9:0010:20. For more information and course materials, please visit http://brylinski.cct.lsu.edu/content/teaching or contact Michal Brylinksi at "mbrylinski AT lsu.edu".


Computational Physics: Computing for Petascale Systems

Taught by: Juana Moreno (LSU) and Karen Tomko (Ohio Supercomputer Center)
Teaching periods: Spring 2011, Spring 2012, Spring 2013, Spring 2014Computational Physics is a threecredit graduate course. It focuses on high performance computing (HPC) and the techniques used in designing and implementing computationally intensive applications on HPC systems. High performance systems including traditional parallel supercomputers, Linux clusters, and heterogeneous computing (such as GPUs and MIC) is discussed. The course focuses on parallelization and memory access optimization for computationally intensive applications in science and engineering. 2014 classes meet Monday, Wednesday, and Friday 8:309:20.
For additional information and course materials, please contact Juana Moreno at morenoatlsu.edu.
Course materials can be found at
http://magnet.phys.lsu.edu/~juana/Syllabus.html


Atomic and Molecular Physics

Taught by: Noa Marom (Tulane)
Teaching periods: Spring 2014In this course we will apply quantum mechanics to study the properties of materials. We will learn how electrons interact to form atoms and molecules. We will introduce the manyelectron problem and explore approximate methods for solving it, including linear combination of atomic orbitals, HartreeFock, and density functional theory (DFT). Students will learn the fundamental physics behind the quantum mechanical computer simulations, which have become one of the essential tools of modern science. They will understand the advantages, limitations, and interrelations of the various theoretical approaches covered. They will understand how theory can answer questions, such as: What materials can exist and with what properties? What is the geometry (bond lengths and angles) of a molecule, solid, or nanostructure? How is the electron density distributed over space? What are the vibrational frequencies of the atomic nuclei in a given material? If time permits, students will acquire hands on experience using a DFT code. Prerequisites: undergraduate quantum mechanics. 2014 classes meet Monday, Wednesday and Friday 10:0010:50. For more information, please contact Noa Marom at nmarom at tulane.edu. * At Tulane the course registration number is PHYS 7160. Classes will meet at the CCS seminar room.


Solid State Physics

Taught by: Adrienn Ruzsinszky (Tulane)
Teaching periods: Fall 2011In Solid State Physics students learn about the different types of solids, their properties, and the concepts and principles underlying solid state physics. The students’ understanding progresses through a sequence of models or approximations, from the simplest to the more detailed and realistic. This course covers subjects such as the Drude and the Sommerfeld theory of metals, the failures of the freeelectron model, crystal and reciprocal lattices,how to determinate crystal structures by Xray diffraction, electrons in a weak periodic potential, tightbinding method, semiclassical model of electron dynamics,Fermi surface, classical and quantum theory of the harmonic crystal and semiconductors.
For additional information and course materials, please contact Adrienn Ruzsinszky at aruzsinszky AT temple.edu
Syllabus (PDF).


Condensed Matter Physics

Taught by: Ilya Vekhter (LSU)
Teaching periods: Spring 2015, Spring 2014, Spring 2013A graduate course taught by Ilya Vekhter aimed at both experiment and theory students working in condensed matter physics. The course focuses on a phenomenological description of ordered phases, especially on magnetism and superconductivity. We will learn how to write the appropriate GinzburgLandau theory for different situations based on symmetry principles. We will then describe ferro and antiferromagnetic orders, structure of the magnetic domains and domain walls, superconductivity, influence of an applied magnetic field on magnetic and superconducting order, and interplay between the two. A connection between the simplest microscopic models and the GinzburgLandau expansion will be discussed. Current technology allows the class to be highly interactive and discussionbased across campuses. 2015 classes meet on Monday, Wednesday, and Friday at 10:3011:20 a.m. For additional information and course materials, please contact Ilya Vekhter at vekhteratlsu.edu.

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